Effects of exclusive breastfeeding on infant gut microbiota: a meta-analysis across studies and populations
Nhan Thi Ho
Wed Apr 04 14:46:28 2018
Summary of included studies
All studies
| ExclusiveBF | Non_exclusiveBF | No_BF | sum | |
|---|---|---|---|---|
| Bangladesh | 138 | 178 | 6 | 322 |
| Canada | 86 | 48 | 33 | 167 |
| Haiti | 37 | 11 | 0 | 48 |
| South Africa | 86 | 57 | 0 | 143 |
| USA(CA_FL) | 150 | 68 | 12 | 230 |
| USA(CA_MA_MO) | 38 | 66 | 116 | 220 |
| USA(NC) | 12 | 8 | 1 | 21 |
| All studies | 547 | 436 | 168 | 1151 |
All studies for stratified meta-analysis by birth mode
| Vaginal | C-section | sum | |
|---|---|---|---|
| Canada | 130 | 37 | 167 |
| Haiti | 42 | 6 | 48 |
| USA(CA_FL) | 162 | 65 | 227 |
| USA(CA_MA_MO) | 150 | 78 | 228 |
| All studies | 484 | 186 | 670 |
Microbiome age
Plot of microbiome age by study all ages
With Generalized additive mixed model (GAMM) fit and 95%CI.
Sample age < 6 months only
Standardized microbiome age and GAMM fit comparison between bf group within each study
Meta-analysis for samples in <= 6 months old infants
Meta-analysis models based on adjusted estimate (adjusted for age of infant at sample collection) and standard error from linear mixed effect models.
Change of RM in non-exclusive breastfed (nebf) vs. exclusive breastfed (exbf)
RD 95%-CI %W(fixed)
Thompson et al 2015 ( USA(NC) ) 0.8754 [ 0.1366; 1.6142] 1.5
Wood et al 2017 ( South Africa ) 0.1214 [-0.2963; 0.5390] 4.7
Pannaraj et al 2017 ( USA(CA_FL) ) 0.2665 [ 0.0464; 0.4866] 17.1
Bender et al 2016 ( Haiti ) -0.1769 [-0.8203; 0.4664] 2.0
Subramanian et al 2014 ( Bangladesh ) 0.0568 [-0.0605; 0.1741] 60.2
Sordillo et al 2017 ( USA(CA_MA_MO) ) 0.7355 [ 0.3600; 1.1109] 5.9
Azad et al 2015 ( Canada ) 0.6149 [ 0.3048; 0.9250] 8.6
%W(random)
Thompson et al 2015 ( USA(NC) ) 7.3
Wood et al 2017 ( South Africa ) 13.4
Pannaraj et al 2017 ( USA(CA_FL) ) 18.7
Bender et al 2016 ( Haiti ) 8.7
Subramanian et al 2014 ( Bangladesh ) 21.0
Sordillo et al 2017 ( USA(CA_MA_MO) ) 14.5
Azad et al 2015 ( Canada ) 16.3
Number of studies combined: k = 7
RD 95%-CI z p-value
Fixed effect model 0.1913 [0.1003; 0.2823] 4.12 < 0.0001
Random effects model 0.3336 [0.0894; 0.5778] 2.68 0.0074
Quantifying heterogeneity:
tau^2 = 0.0702; H = 2.06 [1.42; 2.98]; I^2 = 76.4% [50.4%; 88.8%]
Test of heterogeneity:
Q d.f. p-value
25.40 6 0.0003
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Thompson et al 2015 ( USA(NC) ) | 0.0202100021212404 |
| Wood et al 2017 ( South Africa ) | 0.569010986228987 |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.0176451947099079 |
| Bender et al 2016 ( Haiti ) | 0.589859305402284 |
| Subramanian et al 2014 ( Bangladesh ) | 0.342537683608756 |
| Sordillo et al 2017 ( USA(CA_MA_MO) ) | 0.000123424504683378 |
| Azad et al 2015 ( Canada ) | 0.000101690866421991 |
Sensitivity analysis
No Haiti data
RD 95%-CI %W(fixed)
Thompson et al 2015 ( USA(NC) ) 0.8754 [ 0.1366; 1.6142] 1.5
Wood et al 2017 ( South Africa ) 0.1214 [-0.2963; 0.5390] 4.8
Pannaraj et al 2017 ( USA(CA_FL) ) 0.2665 [ 0.0464; 0.4866] 17.4
Subramanian et al 2014 ( Bangladesh ) 0.0568 [-0.0605; 0.1741] 61.4
Sordillo et al 2017 ( USA(CA_MA_MO) ) 0.7355 [ 0.3600; 1.1109] 6.0
Azad et al 2015 ( Canada ) 0.6149 [ 0.3048; 0.9250] 8.8
%W(random)
Thompson et al 2015 ( USA(NC) ) 8.1
Wood et al 2017 ( South Africa ) 14.8
Pannaraj et al 2017 ( USA(CA_FL) ) 20.4
Subramanian et al 2014 ( Bangladesh ) 22.9
Sordillo et al 2017 ( USA(CA_MA_MO) ) 15.9
Azad et al 2015 ( Canada ) 17.8
Number of studies combined: k = 6
RD 95%-CI z p-value
Fixed effect model 0.1988 [0.1069; 0.2908] 4.24 < 0.0001
Random effects model 0.3835 [0.1247; 0.6422] 2.90 0.0037
Quantifying heterogeneity:
tau^2 = 0.0726; H = 2.20 [1.49; 3.25]; I^2 = 79.3% [54.7%; 90.5%]
Test of heterogeneity:
Q d.f. p-value
24.11 5 0.0002
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Thompson et al 2015 ( USA(NC) ) | 0.0202100021212404 |
| Wood et al 2017 ( South Africa ) | 0.569010986228987 |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.0176451947099079 |
| Subramanian et al 2014 ( Bangladesh ) | 0.342537683608756 |
| Sordillo et al 2017 ( USA(CA_MA_MO) ) | 0.000123424504683378 |
| Azad et al 2015 ( Canada ) | 0.000101690866421991 |
No USA(NC) data
RD 95%-CI %W(fixed)
Wood et al 2017 ( South Africa ) 0.1214 [-0.2963; 0.5390] 4.8
Pannaraj et al 2017 ( USA(CA_FL) ) 0.2665 [ 0.0464; 0.4866] 17.4
Bender et al 2016 ( Haiti ) -0.1769 [-0.8203; 0.4664] 2.0
Subramanian et al 2014 ( Bangladesh ) 0.0568 [-0.0605; 0.1741] 61.1
Sordillo et al 2017 ( USA(CA_MA_MO) ) 0.7355 [ 0.3600; 1.1109] 6.0
Azad et al 2015 ( Canada ) 0.6149 [ 0.3048; 0.9250] 8.7
%W(random)
Wood et al 2017 ( South Africa ) 14.3
Pannaraj et al 2017 ( USA(CA_FL) ) 20.4
Bender et al 2016 ( Haiti ) 9.1
Subramanian et al 2014 ( Bangladesh ) 23.1
Sordillo et al 2017 ( USA(CA_MA_MO) ) 15.5
Azad et al 2015 ( Canada ) 17.6
Number of studies combined: k = 6
RD 95%-CI z p-value
Fixed effect model 0.1808 [0.0891; 0.2725] 3.87 0.0001
Random effects model 0.2909 [0.0458; 0.5360] 2.33 0.0200
Quantifying heterogeneity:
tau^2 = 0.0640; H = 2.10 [1.41; 3.13]; I^2 = 77.3% [49.6%; 89.8%]
Test of heterogeneity:
Q d.f. p-value
22.05 5 0.0005
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Wood et al 2017 ( South Africa ) | 0.569010986228987 |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.0176451947099079 |
| Bender et al 2016 ( Haiti ) | 0.589859305402284 |
| Subramanian et al 2014 ( Bangladesh ) | 0.342537683608756 |
| Sordillo et al 2017 ( USA(CA_MA_MO) ) | 0.000123424504683378 |
| Azad et al 2015 ( Canada ) | 0.000101690866421991 |
No USA(CA_MA_MO) data
RD 95%-CI %W(fixed)
Thompson et al 2015 ( USA(NC) ) 0.8754 [ 0.1366; 1.6142] 1.6
Wood et al 2017 ( South Africa ) 0.1214 [-0.2963; 0.5390] 5.0
Pannaraj et al 2017 ( USA(CA_FL) ) 0.2665 [ 0.0464; 0.4866] 18.2
Bender et al 2016 ( Haiti ) -0.1769 [-0.8203; 0.4664] 2.1
Subramanian et al 2014 ( Bangladesh ) 0.0568 [-0.0605; 0.1741] 63.9
Azad et al 2015 ( Canada ) 0.6149 [ 0.3048; 0.9250] 9.1
%W(random)
Thompson et al 2015 ( USA(NC) ) 7.4
Wood et al 2017 ( South Africa ) 15.0
Pannaraj et al 2017 ( USA(CA_FL) ) 22.8
Bender et al 2016 ( Haiti ) 9.0
Subramanian et al 2014 ( Bangladesh ) 26.7
Azad et al 2015 ( Canada ) 19.0
Number of studies combined: k = 6
RD 95%-CI z p-value
Fixed effect model 0.1574 [0.0636; 0.2512] 3.29 0.0010
Random effects model 0.2602 [0.0267; 0.4936] 2.18 0.0290
Quantifying heterogeneity:
tau^2 = 0.0495; H = 1.83 [1.20; 2.80]; I^2 = 70.3% [30.5%; 87.3%]
Test of heterogeneity:
Q d.f. p-value
16.83 5 0.0048
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Thompson et al 2015 ( USA(NC) ) | 0.0202100021212404 |
| Wood et al 2017 ( South Africa ) | 0.569010986228987 |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.0176451947099079 |
| Bender et al 2016 ( Haiti ) | 0.589859305402284 |
| Subramanian et al 2014 ( Bangladesh ) | 0.342537683608756 |
| Azad et al 2015 ( Canada ) | 0.000101690866421991 |
Stratify by birth mode (not standardized)
Vaginal
RD 95%-CI %W(fixed)
Azad et al 2015 (Canada) 2.0223 [ 1.0746; 2.9701] 23.9
Bender et al 2016 (Haiti) -0.5119 [-2.7851; 1.7614] 4.1
Pannaraj et al 2017 (USA(CA_FL)) 0.5934 [-0.0958; 1.2826] 45.1
Sordillo et al 2017 (USA(CA_MA_MO)) 1.5749 [ 0.6821; 2.4677] 26.9
%W(random)
Azad et al 2015 (Canada) 27.7
Bender et al 2016 (Haiti) 10.8
Pannaraj et al 2017 (USA(CA_FL)) 32.8
Sordillo et al 2017 (USA(CA_MA_MO)) 28.8
Number of studies combined: k = 4
RD 95%-CI z p-value
Fixed effect model 1.1523 [0.6894; 1.6152] 4.88 < 0.0001
Random effects model 1.1519 [0.2829; 2.0209] 2.60 0.0094
Quantifying heterogeneity:
tau^2 = 0.4763; H = 1.70 [1.00; 2.92]; I^2 = 65.4% [0.0%; 88.2%]
Test of heterogeneity:
Q d.f. p-value
8.68 3 0.0338
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Azad et al 2015 (Canada) | 2.88635033937751e-05 |
| Bender et al 2016 (Haiti) | 0.658981004403214 |
| Pannaraj et al 2017 (USA(CA_FL)) | 0.0914811823311381 |
| Sordillo et al 2017 (USA(CA_MA_MO)) | 0.000545678208685348 |
C-section
RD 95%-CI %W(fixed)
Azad et al 2015 (Canada) 0.6820 [-1.3391; 2.7031] 14.4
Bender et al 2016 (Haiti) -0.3508 [-4.3974; 3.6958] 3.6
Pannaraj et al 2017 (USA(CA_FL)) 0.7880 [-0.2996; 1.8755] 49.7
Sordillo et al 2017 (USA(CA_MA_MO)) 1.1977 [-0.1522; 2.5476] 32.3
%W(random)
Azad et al 2015 (Canada) 14.4
Bender et al 2016 (Haiti) 3.6
Pannaraj et al 2017 (USA(CA_FL)) 49.7
Sordillo et al 2017 (USA(CA_MA_MO)) 32.3
Number of studies combined: k = 4
RD 95%-CI z p-value
Fixed effect model 0.8641 [0.0971; 1.6310] 2.21 0.0272
Random effects model 0.8641 [0.0971; 1.6310] 2.21 0.0272
Quantifying heterogeneity:
tau^2 = 0; H = 1.00 [1.00; 1.17]; I^2 = 0.0% [0.0%; 27.2%]
Test of heterogeneity:
Q d.f. p-value
0.63 3 0.8893
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Azad et al 2015 (Canada) | 0.508396867999409 |
| Bender et al 2016 (Haiti) | 0.865079808120753 |
| Pannaraj et al 2017 (USA(CA_FL)) | 0.155598040795797 |
| Sordillo et al 2017 (USA(CA_MA_MO)) | 0.0820319111581724 |
Trend of microbiome age in exclusive breastfed (exbf), non-exclusive breastfed (nebf) and no bf
RD 95%-CI %W(fixed)
Subramanian et al 2014 (Bangladesh) 0.0308 [-0.0757; 0.1372] 44.1
Azad et al 2015 (Canada) 0.5818 [ 0.4102; 0.7534] 17.0
Pannaraj et al 2017 (USA(CA_FL)) 0.3161 [ 0.1504; 0.4819] 18.2
Sordillo et al 2017 (USA(CA_MA_MO)) 0.5214 [ 0.3626; 0.6802] 19.8
Thompson et al 2015 (USA(NC)) 0.2911 [-0.4807; 1.0628] 0.8
%W(random)
Subramanian et al 2014 (Bangladesh) 24.0
Azad et al 2015 (Canada) 22.6
Pannaraj et al 2017 (USA(CA_FL)) 22.7
Sordillo et al 2017 (USA(CA_MA_MO)) 22.9
Thompson et al 2015 (USA(NC)) 7.8
Number of studies combined: k = 5
RD 95%-CI z p-value
Fixed effect model 0.2758 [0.2051; 0.3465] 7.64 < 0.0001
Random effects model 0.3526 [0.0926; 0.6125] 2.66 0.0079
Quantifying heterogeneity:
tau^2 = 0.0703; H = 3.24 [2.28; 4.61]; I^2 = 90.5% [80.7%; 95.3%]
Test of heterogeneity:
Q d.f. p-value
41.99 4 < 0.0001
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Subramanian et al 2014 (Bangladesh) | 0.570837554151296 |
| Azad et al 2015 (Canada) | 2.9999698377109e-11 |
| Pannaraj et al 2017 (USA(CA_FL)) | 0.000185565976276297 |
| Sordillo et al 2017 (USA(CA_MA_MO)) | 1.24192582145007e-10 |
| Thompson et al 2015 (USA(NC)) | 0.459754398037424 |
Exploratory analysis for effect of duration of exbf, formula and solid intro
With GAMM fit and 95%CI.
Subramanian (Bangladesh) data
Number of infants by duration of bf in the test set
<=2 months >2 months
26 13 Number of samples by duration of bf in the test set
<=2 months >2 months
483 252 Number of samples by duration of bf in the test set (>6 months only)
<=2 months >2 months
305 176 Duration (month) of exbf
Test for age > 6 months and <15months GAM part
| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | 11.516456 | 0.4287802 | 26.858644 | 0.0000000 |
| month.exbf2>2 months | -1.634246 | 0.7401967 | -2.207854 | 0.0280084 |
| edf | Ref.df | F | p-value | |
|---|---|---|---|---|
| s(age.sample):month.exbf2<=2 months | 1.000001 | 1.000001 | 120.79393 | 0 |
| s(age.sample):month.exbf2>2 months | 1.000000 | 1.000000 | 60.88972 | 0 |
LME part
| Value | Std.Error | DF | t-value | p-value | |
|---|---|---|---|---|---|
| X(Intercept) | 11.516456 | 0.4302022 | 264 | 26.769865 | 0.0000000 |
| Xmonth.exbf2>2 months | -1.634246 | 0.7426508 | 37 | -2.200557 | 0.0340874 |
| Xs(age.sample):month.exbf2<=2 monthsFx1 | 2.352653 | 0.2147700 | 264 | 10.954291 | 0.0000000 |
| Xs(age.sample):month.exbf2>2 monthsFx1 | 2.231823 | 0.2869630 | 264 | 7.777391 | 0.0000000 |
Performance of the Random Forest model to estimate microbiome age
Evaluated on the training and test set of Subramanian (Bangladesh) data.
Alpha diversity indexes
Plots of alpha diversity by study by age
With GAMM fit and 95%CI.
Samples <= 6 months only
GAMM fit comparison between bf group within each study
Samples <=6 months only
Exploration by duration of exclusive bf
Subramanian (Bangladesh) data only.
Exclusive bf duration
Shannon index.
Meta-analysis
For samples <=6 months old only.
Change in non-exbf vs. exbf
Chao1
RD 95%-CI %W(fixed)
Subramanian et al 2014 ( Bangladesh ) 0.0677 [-0.0136; 0.1491] 79.0
Azad et al 2015 ( Canada ) 0.3752 [ 0.0596; 0.6908] 5.3
Bender et al 2016 ( Haiti ) 0.4922 [-0.3266; 1.3110] 0.8
Wood et al 2017 ( South Africa ) 0.5113 [ 0.0923; 0.9303] 3.0
Pannaraj et al 2017 ( USA(CA_FL) ) 0.1201 [-0.1362; 0.3764] 8.0
Sordillo et al 2017 ( USA(CA_MA_MO) ) 0.6457 [ 0.2430; 1.0485] 3.2
Thompson et al 2015 ( USA(NC) ) 0.4111 [-0.4054; 1.2277] 0.8
%W(random)
Subramanian et al 2014 ( Bangladesh ) 28.0
Azad et al 2015 ( Canada ) 16.8
Bender et al 2016 ( Haiti ) 4.9
Wood et al 2017 ( South Africa ) 12.6
Pannaraj et al 2017 ( USA(CA_FL) ) 19.6
Sordillo et al 2017 ( USA(CA_MA_MO) ) 13.2
Thompson et al 2015 ( USA(NC) ) 4.9
Number of studies combined: k = 7
RD 95%-CI z p-value
Fixed effect model 0.1259 [0.0536; 0.1982] 3.41 0.0006
Random effects model 0.2995 [0.1020; 0.4969] 2.97 0.0030
Quantifying heterogeneity:
tau^2 = 0.0346; H = 1.59 [1.05; 2.41]; I^2 = 60.7% [9.9%; 82.8%]
Test of heterogeneity:
Q d.f. p-value
15.25 6 0.0184
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Subramanian et al 2014 ( Bangladesh ) | 0.102847325927163 |
| Azad et al 2015 ( Canada ) | 0.01980051110656 |
| Bender et al 2016 ( Haiti ) | 0.238756122389415 |
| Wood et al 2017 ( South Africa ) | 0.0167677830041401 |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.358399385859461 |
| Sordillo et al 2017 ( USA(CA_MA_MO) ) | 0.00167635766494574 |
| Thompson et al 2015 ( USA(NC) ) | 0.32371285335117 |
Observed_species
RD 95%-CI %W(fixed)
Subramanian et al 2014 ( Bangladesh ) 0.0673 [-0.0127; 0.1473] 77.1
Azad et al 2015 ( Canada ) 0.3721 [ 0.0590; 0.6852] 5.0
Bender et al 2016 ( Haiti ) 0.4601 [-0.3413; 1.2616] 0.8
Wood et al 2017 ( South Africa ) 0.4996 [ 0.0848; 0.9143] 2.9
Pannaraj et al 2017 ( USA(CA_FL) ) 0.1447 [-0.0763; 0.3657] 10.1
Sordillo et al 2017 ( USA(CA_MA_MO) ) 0.6461 [ 0.2454; 1.0467] 3.1
Thompson et al 2015 ( USA(NC) ) 0.3555 [-0.3448; 1.0557] 1.0
%W(random)
Subramanian et al 2014 ( Bangladesh ) 28.2
Azad et al 2015 ( Canada ) 16.1
Bender et al 2016 ( Haiti ) 4.5
Wood et al 2017 ( South Africa ) 12.0
Pannaraj et al 2017 ( USA(CA_FL) ) 21.0
Sordillo et al 2017 ( USA(CA_MA_MO) ) 12.5
Thompson et al 2015 ( USA(NC) ) 5.7
Number of studies combined: k = 7
RD 95%-CI z p-value
Fixed effect model 0.1266 [0.0564; 0.1969] 3.53 0.0004
Random effects model 0.2909 [0.1053; 0.4765] 3.07 0.0021
Quantifying heterogeneity:
tau^2 = 0.0301; H = 1.59 [1.05; 2.41]; I^2 = 60.4% [9.1%; 82.7%]
Test of heterogeneity:
Q d.f. p-value
15.14 6 0.0192
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Subramanian et al 2014 ( Bangladesh ) | 0.0990100956520888 |
| Azad et al 2015 ( Canada ) | 0.019839103185688 |
| Bender et al 2016 ( Haiti ) | 0.260501865374435 |
| Wood et al 2017 ( South Africa ) | 0.0182288177251842 |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.19952096913775 |
| Sordillo et al 2017 ( USA(CA_MA_MO) ) | 0.00157427402976728 |
| Thompson et al 2015 ( USA(NC) ) | 0.319751771051308 |
Pd_whole_tree
RD 95%-CI %W(fixed)
Subramanian et al 2014 ( Bangladesh ) 0.0953 [ 0.0196; 0.1710] 80.5
Azad et al 2015 ( Canada ) 0.2877 [-0.0327; 0.6082] 4.5
Bender et al 2016 ( Haiti ) 0.3082 [-0.3766; 0.9931] 1.0
Wood et al 2017 ( South Africa ) 0.4724 [ 0.0489; 0.8958] 2.6
Pannaraj et al 2017 ( USA(CA_FL) ) 0.2168 [ 0.0121; 0.4215] 11.0
Thompson et al 2015 ( USA(NC) ) 0.7261 [-0.2385; 1.6906] 0.5
%W(random)
Subramanian et al 2014 ( Bangladesh ) 52.8
Azad et al 2015 ( Canada ) 12.0
Bender et al 2016 ( Haiti ) 3.1
Wood et al 2017 ( South Africa ) 7.4
Pannaraj et al 2017 ( USA(CA_FL) ) 23.2
Thompson et al 2015 ( USA(NC) ) 1.6
Number of studies combined: k = 6
RD 95%-CI z p-value
Fixed effect model 0.1322 [0.0643; 0.2001] 3.82 0.0001
Random effects model 0.1910 [0.0685; 0.3134] 3.06 0.0022
Quantifying heterogeneity:
tau^2 = 0.0059; H = 1.15 [1.00; 1.78]; I^2 = 25.0% [0.0%; 68.4%]
Test of heterogeneity:
Q d.f. p-value
6.66 5 0.2469
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Subramanian et al 2014 ( Bangladesh ) | 0.0136266394489582 |
| Azad et al 2015 ( Canada ) | 0.0784131649118116 |
| Bender et al 2016 ( Haiti ) | 0.377692577417145 |
| Wood et al 2017 ( South Africa ) | 0.0288048675369895 |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.0379096968161372 |
| Thompson et al 2015 ( USA(NC) ) | 0.140133230873501 |
Shannon
RD 95%-CI %W(fixed)
Subramanian et al 2014 ( Bangladesh ) 0.2592 [ 0.1185; 0.3999] 57.3
Azad et al 2015 ( Canada ) 0.3262 [ 0.0159; 0.6365] 11.8
Bender et al 2016 ( Haiti ) -0.1146 [-0.7954; 0.5662] 2.4
Wood et al 2017 ( South Africa ) 0.3071 [-0.1311; 0.7452] 5.9
Pannaraj et al 2017 ( USA(CA_FL) ) 0.3732 [ 0.0808; 0.6657] 13.3
Sordillo et al 2017 ( USA(CA_MA_MO) ) 0.7684 [ 0.3821; 1.1546] 7.6
Thompson et al 2015 ( USA(NC) ) 0.3001 [-0.5308; 1.1310] 1.6
%W(random)
Subramanian et al 2014 ( Bangladesh ) 40.5
Azad et al 2015 ( Canada ) 15.7
Bender et al 2016 ( Haiti ) 4.0
Wood et al 2017 ( South Africa ) 8.9
Pannaraj et al 2017 ( USA(CA_FL) ) 17.2
Sordillo et al 2017 ( USA(CA_MA_MO) ) 11.0
Thompson et al 2015 ( USA(NC) ) 2.7
Number of studies combined: k = 7
RD 95%-CI z p-value
Fixed effect model 0.3153 [0.2088; 0.4219] 5.80 < 0.0001
Random effects model 0.3359 [0.1959; 0.4759] 4.70 < 0.0001
Quantifying heterogeneity:
tau^2 = 0.0074; H = 1.12 [1.00; 1.67]; I^2 = 20.9% [0.0%; 64.3%]
Test of heterogeneity:
Q d.f. p-value
7.59 6 0.2700
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Subramanian et al 2014 ( Bangladesh ) | 0.000305463231694058 |
| Azad et al 2015 ( Canada ) | 0.0393559233405728 |
| Bender et al 2016 ( Haiti ) | 0.74142212926805 |
| Wood et al 2017 ( South Africa ) | 0.169568310346119 |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.0123688713005407 |
| Sordillo et al 2017 ( USA(CA_MA_MO) ) | 9.65594918082499e-05 |
| Thompson et al 2015 ( USA(NC) ) | 0.479014124949741 |
Sensitivity analysis Change in non-exbf vs. exbf
Show the results of Shannon indexes only.
No Haiti data
RD 95%-CI %W(fixed)
Subramanian et al 2014 ( Bangladesh ) 0.2592 [ 0.1185; 0.3999] 58.8
Azad et al 2015 ( Canada ) 0.3262 [ 0.0159; 0.6365] 12.1
Wood et al 2017 ( South Africa ) 0.3071 [-0.1311; 0.7452] 6.1
Pannaraj et al 2017 ( USA(CA_FL) ) 0.3732 [ 0.0808; 0.6657] 13.6
Sordillo et al 2017 ( USA(CA_MA_MO) ) 0.7684 [ 0.3821; 1.1546] 7.8
Thompson et al 2015 ( USA(NC) ) 0.3001 [-0.5308; 1.1310] 1.7
%W(random)
Subramanian et al 2014 ( Bangladesh ) 45.8
Azad et al 2015 ( Canada ) 15.5
Wood et al 2017 ( South Africa ) 8.5
Pannaraj et al 2017 ( USA(CA_FL) ) 17.1
Sordillo et al 2017 ( USA(CA_MA_MO) ) 10.6
Thompson et al 2015 ( USA(NC) ) 2.5
Number of studies combined: k = 6
RD 95%-CI z p-value
Fixed effect model 0.3261 [0.2183; 0.4340] 5.93 < 0.0001
Random effects model 0.3483 [0.2145; 0.4821] 5.10 < 0.0001
Quantifying heterogeneity:
tau^2 = 0.0050; H = 1.10 [1.00; 1.61]; I^2 = 16.9% [0.0%; 61.6%]
Test of heterogeneity:
Q d.f. p-value
6.02 5 0.3047
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Subramanian et al 2014 ( Bangladesh ) | 0.000305463231694058 |
| Azad et al 2015 ( Canada ) | 0.0393559233405728 |
| Wood et al 2017 ( South Africa ) | 0.169568310346119 |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.0123688713005407 |
| Sordillo et al 2017 ( USA(CA_MA_MO) ) | 9.65594918082499e-05 |
| Thompson et al 2015 ( USA(NC) ) | 0.479014124949741 |
No UNC data
RD 95%-CI %W(fixed)
Subramanian et al 2014 ( Bangladesh ) 0.2592 [ 0.1185; 0.3999] 58.3
Azad et al 2015 ( Canada ) 0.3262 [ 0.0159; 0.6365] 12.0
Bender et al 2016 ( Haiti ) -0.1146 [-0.7954; 0.5662] 2.5
Wood et al 2017 ( South Africa ) 0.3071 [-0.1311; 0.7452] 6.0
Pannaraj et al 2017 ( USA(CA_FL) ) 0.3732 [ 0.0808; 0.6657] 13.5
Sordillo et al 2017 ( USA(CA_MA_MO) ) 0.7684 [ 0.3821; 1.1546] 7.7
%W(random)
Subramanian et al 2014 ( Bangladesh ) 36.5
Azad et al 2015 ( Canada ) 17.2
Bender et al 2016 ( Haiti ) 4.9
Wood et al 2017 ( South Africa ) 10.3
Pannaraj et al 2017 ( USA(CA_FL) ) 18.6
Sordillo et al 2017 ( USA(CA_MA_MO) ) 12.6
Number of studies combined: k = 6
RD 95%-CI z p-value
Fixed effect model 0.3156 [0.2082; 0.4230] 5.76 < 0.0001
Random effects model 0.3427 [0.1851; 0.5004] 4.26 < 0.0001
Quantifying heterogeneity:
tau^2 = 0.0126; H = 1.23 [1.00; 1.94]; I^2 = 34.1% [0.0%; 73.5%]
Test of heterogeneity:
Q d.f. p-value
7.58 5 0.1807
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Subramanian et al 2014 ( Bangladesh ) | 0.000305463231694058 |
| Azad et al 2015 ( Canada ) | 0.0393559233405728 |
| Bender et al 2016 ( Haiti ) | 0.74142212926805 |
| Wood et al 2017 ( South Africa ) | 0.169568310346119 |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.0123688713005407 |
| Sordillo et al 2017 ( USA(CA_MA_MO) ) | 9.65594918082499e-05 |
No USA(CA_MA_MO) data
RD 95%-CI %W(fixed)
Subramanian et al 2014 ( Bangladesh ) 0.2592 [ 0.1185; 0.3999] 62.0
Azad et al 2015 ( Canada ) 0.3262 [ 0.0159; 0.6365] 12.8
Bender et al 2016 ( Haiti ) -0.1146 [-0.7954; 0.5662] 2.7
Wood et al 2017 ( South Africa ) 0.3071 [-0.1311; 0.7452] 6.4
Pannaraj et al 2017 ( USA(CA_FL) ) 0.3732 [ 0.0808; 0.6657] 14.4
Thompson et al 2015 ( USA(NC) ) 0.3001 [-0.5308; 1.1310] 1.8
%W(random)
Subramanian et al 2014 ( Bangladesh ) 62.0
Azad et al 2015 ( Canada ) 12.8
Bender et al 2016 ( Haiti ) 2.7
Wood et al 2017 ( South Africa ) 6.4
Pannaraj et al 2017 ( USA(CA_FL) ) 14.4
Thompson et al 2015 ( USA(NC) ) 1.8
Number of studies combined: k = 6
RD 95%-CI z p-value
Fixed effect model 0.2780 [0.1672; 0.3889] 4.92 < 0.0001
Random effects model 0.2780 [0.1672; 0.3889] 4.92 < 0.0001
Quantifying heterogeneity:
tau^2 = 0; H = 1.00 [1.00; 1.21]; I^2 = 0.0% [0.0%; 32.0%]
Test of heterogeneity:
Q d.f. p-value
1.87 5 0.8674
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Subramanian et al 2014 ( Bangladesh ) | 0.000305463231694058 |
| Azad et al 2015 ( Canada ) | 0.0393559233405728 |
| Bender et al 2016 ( Haiti ) | 0.74142212926805 |
| Wood et al 2017 ( South Africa ) | 0.169568310346119 |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.0123688713005407 |
| Thompson et al 2015 ( USA(NC) ) | 0.479014124949741 |
Stratify by birth mode for Change in non-exbf vs. exbf (not standardized)
Show results of Shannon index only.
Vaginal
RD 95%-CI %W(fixed)
Azad et al 2015 (Canada) 0.1424 [-0.0984; 0.3832] 40.8
Bender et al 2016 (Haiti) -0.2018 [-0.9752; 0.5715] 4.0
Pannaraj et al 2017 (USA(CA_FL)) 0.3734 [ 0.1294; 0.6174] 39.7
Sordillo et al 2017 (USA(CA_MA_MO)) 0.4321 [ 0.0420; 0.8223] 15.5
%W(random)
Azad et al 2015 (Canada) 38.3
Bender et al 2016 (Haiti) 5.4
Pannaraj et al 2017 (USA(CA_FL)) 37.6
Sordillo et al 2017 (USA(CA_MA_MO)) 18.6
Number of studies combined: k = 4
RD 95%-CI z p-value
Fixed effect model 0.2656 [0.1118; 0.4194] 3.38 0.0007
Random effects model 0.2647 [0.0798; 0.4495] 2.81 0.0050
Quantifying heterogeneity:
tau^2 = 0.0081; H = 1.13 [1.00; 2.90]; I^2 = 22.3% [0.0%; 88.1%]
Test of heterogeneity:
Q d.f. p-value
3.86 3 0.2771
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Azad et al 2015 (Canada) | 0.246532761397953 |
| Bender et al 2016 (Haiti) | 0.608996225108868 |
| Pannaraj et al 2017 (USA(CA_FL)) | 0.00270151112577258 |
| Sordillo et al 2017 (USA(CA_MA_MO)) | 0.0299341350698865 |
C-section
RD 95%-CI %W(fixed)
Azad et al 2015 (Canada) 0.4873 [ 0.0230; 0.9515] 40.3
Pannaraj et al 2017 (USA(CA_FL)) -0.0737 [-0.5869; 0.4395] 33.0
Sordillo et al 2017 (USA(CA_MA_MO)) 1.0833 [ 0.5127; 1.6540] 26.7
%W(random)
Azad et al 2015 (Canada) 34.9
Pannaraj et al 2017 (USA(CA_FL)) 33.4
Sordillo et al 2017 (USA(CA_MA_MO)) 31.7
Number of studies combined: k = 3
RD 95%-CI z p-value
Fixed effect model 0.4612 [ 0.1665; 0.7560] 3.07 0.0022
Random effects model 0.4888 [-0.1327; 1.1103] 1.54 0.1232
Quantifying heterogeneity:
tau^2 = 0.2323; H = 2.09 [1.16; 3.77]; I^2 = 77.1% [25.6%; 93.0%]
Test of heterogeneity:
Q d.f. p-value
8.75 2 0.0126
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Azad et al 2015 (Canada) | 0.0396622679428872 |
| Pannaraj et al 2017 (USA(CA_FL)) | 0.778417002121859 |
| Sordillo et al 2017 (USA(CA_MA_MO)) | 0.000198560001433614 |
Put meta-analysis results (random models) of all indexes together
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| shannon | 0.3359260 | 0.0714283 | 0.1959290 | 0.4759229 | 4.702980 | 0.0000026 | 0.0000103 |
| observed_species | 0.2908894 | 0.0946918 | 0.1052969 | 0.4764819 | 3.071960 | 0.0021266 | 0.0029552 |
| pd_whole_tree | 0.1909514 | 0.0624970 | 0.0684595 | 0.3134432 | 3.055369 | 0.0022478 | 0.0029552 |
| chao1 | 0.2994547 | 0.1007464 | 0.1019953 | 0.4969141 | 2.972360 | 0.0029552 | 0.0029552 |
Trend effect in exbf, non-exbf, no bf
Chao1
RD 95%-CI %W(fixed)
Subramanian et al 2014 ( Bangladesh ) 0.0550 [-0.0189; 0.1289] 65.2
Azad et al 2015 ( Canada ) 0.5725 [ 0.3986; 0.7464] 11.8
Bender et al 2016 ( Haiti ) NA 0.0
Wood et al 2017 ( South Africa ) NA 0.0
Pannaraj et al 2017 ( USA(CA_FL) ) 0.1302 [-0.0599; 0.3202] 9.9
Sordillo et al 2017 ( USA(CA_MA_MO) ) 0.4245 [ 0.2553; 0.5937] 12.4
Thompson et al 2015 ( USA(NC) ) 0.4233 [-0.2687; 1.1153] 0.7
%W(random)
Subramanian et al 2014 ( Bangladesh ) 24.7
Azad et al 2015 ( Canada ) 22.4
Bender et al 2016 ( Haiti ) 0.0
Wood et al 2017 ( South Africa ) 0.0
Pannaraj et al 2017 ( USA(CA_FL) ) 21.9
Sordillo et al 2017 ( USA(CA_MA_MO) ) 22.6
Thompson et al 2015 ( USA(NC) ) 8.3
Number of studies combined: k = 5
RD 95%-CI z p-value
Fixed effect model 0.1720 [0.1123; 0.2316] 5.65 < 0.0001
Random effects model 0.3016 [0.0580; 0.5451] 2.43 0.0152
Quantifying heterogeneity:
tau^2 = 0.0610; H = 3.13 [2.19; 4.49]; I^2 = 89.8% [79.1%; 95.0%]
Test of heterogeneity:
Q d.f. p-value
39.26 4 < 0.0001
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Subramanian et al 2014 ( Bangladesh ) | 0.144460866036347 |
| Azad et al 2015 ( Canada ) | 1.0991009354299e-10 |
| Bender et al 2016 ( Haiti ) | NA |
| Wood et al 2017 ( South Africa ) | NA |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.179455833167877 |
| Sordillo et al 2017 ( USA(CA_MA_MO) ) | 8.77670396356771e-07 |
| Thompson et al 2015 ( USA(NC) ) | 0.230600549600578 |
Observed_species
RD 95%-CI %W(fixed)
Subramanian et al 2014 ( Bangladesh ) 0.0603 [-0.0124; 0.1329] 63.5
Azad et al 2015 ( Canada ) 0.5895 [ 0.4168; 0.7623] 11.2
Bender et al 2016 ( Haiti ) NA 0.0
Wood et al 2017 ( South Africa ) NA 0.0
Pannaraj et al 2017 ( USA(CA_FL) ) 0.1163 [-0.0479; 0.2806] 12.4
Sordillo et al 2017 ( USA(CA_MA_MO) ) 0.4610 [ 0.2928; 0.6291] 11.9
Thompson et al 2015 ( USA(NC) ) 0.3661 [-0.2275; 0.9598] 1.0
%W(random)
Subramanian et al 2014 ( Bangladesh ) 24.1
Azad et al 2015 ( Canada ) 21.9
Bender et al 2016 ( Haiti ) 0.0
Wood et al 2017 ( South Africa ) 0.0
Pannaraj et al 2017 ( USA(CA_FL) ) 22.1
Sordillo et al 2017 ( USA(CA_MA_MO) ) 22.0
Thompson et al 2015 ( USA(NC) ) 10.0
Number of studies combined: k = 5
RD 95%-CI z p-value
Fixed effect model 0.1772 [0.1192; 0.2351] 6.00 < 0.0001
Random effects model 0.3070 [0.0641; 0.5500] 2.48 0.0133
Quantifying heterogeneity:
tau^2 = 0.0625; H = 3.30 [2.33; 4.69]; I^2 = 90.8% [81.6%; 95.4%]
Test of heterogeneity:
Q d.f. p-value
43.68 4 < 0.0001
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Subramanian et al 2014 ( Bangladesh ) | 0.104033167825551 |
| Azad et al 2015 ( Canada ) | 2.26960893212611e-11 |
| Bender et al 2016 ( Haiti ) | NA |
| Wood et al 2017 ( South Africa ) | NA |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.165000455562882 |
| Sordillo et al 2017 ( USA(CA_MA_MO) ) | 7.73447284594136e-08 |
| Thompson et al 2015 ( USA(NC) ) | 0.226684364502839 |
Pd_whole_tree
RD 95%-CI %W(fixed)
Subramanian et al 2014 ( Bangladesh ) 0.0646 [-0.0047; 0.1338] 72.9
Azad et al 2015 ( Canada ) 0.5311 [ 0.3540; 0.7082] 11.2
Bender et al 2016 ( Haiti ) NA 0.0
Wood et al 2017 ( South Africa ) NA 0.0
Pannaraj et al 2017 ( USA(CA_FL) ) 0.2032 [ 0.0523; 0.3541] 15.4
Thompson et al 2015 ( USA(NC) ) 0.8566 [ 0.0509; 1.6623] 0.5
%W(random)
Subramanian et al 2014 ( Bangladesh ) 32.9
Azad et al 2015 ( Canada ) 29.1
Bender et al 2016 ( Haiti ) 0.0
Wood et al 2017 ( South Africa ) 0.0
Pannaraj et al 2017 ( USA(CA_FL) ) 30.2
Thompson et al 2015 ( USA(NC) ) 7.8
Number of studies combined: k = 4
RD 95%-CI z p-value
Fixed effect model 0.1422 [0.0830; 0.2013] 4.71 < 0.0001
Random effects model 0.3037 [0.0475; 0.5598] 2.32 0.0202
Quantifying heterogeneity:
tau^2 = 0.0506; H = 3.00 [1.97; 4.57]; I^2 = 88.9% [74.2%; 95.2%]
Test of heterogeneity:
Q d.f. p-value
26.99 3 < 0.0001
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Subramanian et al 2014 ( Bangladesh ) | 0.0676383461236607 |
| Azad et al 2015 ( Canada ) | 4.17049539317814e-09 |
| Bender et al 2016 ( Haiti ) | NA |
| Wood et al 2017 ( South Africa ) | NA |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.00831447939658577 |
| Thompson et al 2015 ( USA(NC) ) | 0.0371791605971582 |
Shannon
RD 95%-CI %W(fixed)
Subramanian et al 2014 ( Bangladesh ) 0.2131 [ 0.0843; 0.3420] 39.0
Azad et al 2015 ( Canada ) 0.5872 [ 0.4153; 0.7590] 21.9
Pannaraj et al 2017 ( USA(CA_FL) ) 0.2570 [ 0.0375; 0.4765] 13.5
Sordillo et al 2017 ( USA(CA_MA_MO) ) 0.5660 [ 0.4038; 0.7282] 24.6
Thompson et al 2015 ( USA(NC) ) -0.0180 [-0.8408; 0.8049] 1.0
%W(random)
Subramanian et al 2014 ( Bangladesh ) 25.8
Azad et al 2015 ( Canada ) 23.8
Pannaraj et al 2017 ( USA(CA_FL) ) 21.4
Sordillo et al 2017 ( USA(CA_MA_MO) ) 24.2
Thompson et al 2015 ( USA(NC) ) 4.8
Number of studies combined: k = 5
RD 95%-CI z p-value
Fixed effect model 0.3858 [0.3053; 0.4663] 9.39 < 0.0001
Random effects model 0.3857 [0.1872; 0.5843] 3.81 0.0001
Quantifying heterogeneity:
tau^2 = 0.0355; H = 2.19 [1.42; 3.37]; I^2 = 79.1% [50.4%; 91.2%]
Test of heterogeneity:
Q d.f. p-value
19.16 4 0.0007
Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2| study | pval |
|---|---|
| Subramanian et al 2014 ( Bangladesh ) | 0.00119013497616748 |
| Azad et al 2015 ( Canada ) | 2.14964602978342e-11 |
| Pannaraj et al 2017 ( USA(CA_FL) ) | 0.0217486284946625 |
| Sordillo et al 2017 ( USA(CA_MA_MO) ) | 7.9318409863511e-12 |
| Thompson et al 2015 ( USA(NC) ) | 0.965887658685873 |
Put meta-analysis results (random models) of all indexes together
| estimate.conbf | se.conbf | ll.conbf | ul.conbf | z.conbf | p.conbf | p.adjust.conbf | |
|---|---|---|---|---|---|---|---|
| shannon | 0.3857475 | 0.1012964 | 0.1872101 | 0.5842849 | 3.808105 | 0.0001400 | 0.0005601 |
| observed_species | 0.3070476 | 0.1239712 | 0.0640686 | 0.5500267 | 2.476766 | 0.0132579 | 0.0201585 |
| pd_whole_tree | 0.3036608 | 0.1306976 | 0.0474982 | 0.5598233 | 2.323384 | 0.0201585 | 0.0201585 |
| chao1 | 0.3015700 | 0.1242513 | 0.0580420 | 0.5450980 | 2.427098 | 0.0152201 | 0.0201585 |
Meta-analysis of taxa relative abundance
Results of 7 studies.
For samples <= 6 months old only in all studies (note for USA(NC) study: GAMLSS BEZI with random subject effect could not run on very small sample size=> did not include subject random effect). Results of random meta-analysis models for taxa available in at least >50% of studies based on adjusted estimates and standard errors from GAMLSS models with zero-inflated beta family adjusted for infant age at sample collection.
Meta-analysis of Change in non-exbf vs. exbf adjusted for age
GAMLSS models with zero-inflated beta family
Phylum (l2)
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes | 0.2477163 | 0.0684909 | 0.1134765 | 0.3819560 | 3.616776 | 0.0002983 | 0.0017898 |
| k__bacteria.p__bacteroidetes | 0.2079683 | 0.0756683 | 0.0596613 | 0.3562754 | 2.748422 | 0.0059883 | 0.0179648 |
Nice plot
Order (l4)
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales | 0.3015251 | 0.0904382 | 0.1242695 | 0.4787808 | 3.334046 | 0.0008559 | 0.0105564 |
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales | 0.2100511 | 0.0757620 | 0.0615603 | 0.3585419 | 2.772512 | 0.0055625 | 0.0369277 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales | 0.2005008 | 0.0896354 | 0.0248186 | 0.3761830 | 2.236847 | 0.0252963 | 0.1169955 |
Nice plot
Family (l5)
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae | 0.2311548 | 0.0856673 | 0.0632499 | 0.3990596 | 2.698284 | 0.0069698 | 0.0756721 |
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales.f__bacteroidaceae | 0.2107748 | 0.0807013 | 0.0526031 | 0.3689465 | 2.611789 | 0.0090070 | 0.0855663 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae | 0.2005008 | 0.0896354 | 0.0248186 | 0.3761830 | 2.236847 | 0.0252963 | 0.1747746 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__clostridiaceae | 0.1652266 | 0.0841374 | 0.0003203 | 0.3301328 | 1.963771 | 0.0495566 | 0.3086619 |
Nice plot
Genus (l6)
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae.g__.eubacterium. | 0.3926058 | 0.1237182 | 0.1501225 | 0.6350890 | 3.173387 | 0.0015067 | 0.0561251 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae.g__megasphaera | 0.4000827 | 0.1416041 | 0.1225438 | 0.6776217 | 2.825361 | 0.0047227 | 0.1115318 |
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales.f__bacteroidaceae.g__bacteroides | 0.2107748 | 0.0807013 | 0.0526031 | 0.3689465 | 2.611789 | 0.0090070 | 0.1220036 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__clostridium | 0.3454360 | 0.1505929 | 0.0502793 | 0.6405927 | 2.293839 | 0.0217997 | 0.2512768 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae.g__veillonella | 0.2136555 | 0.1033136 | 0.0111645 | 0.4161465 | 2.068028 | 0.0386374 | 0.3598107 |
Nice plot
Sensitivity meta-analysis of Change in non-exbf vs. exbf adjusted for age
No UNC data
l2
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes | 0.2469023 | 0.0691970 | 0.1112786 | 0.3825259 | 3.568106 | 0.0003596 | 0.0025170 |
| k__bacteria.p__bacteroidetes | 0.1932696 | 0.0763734 | 0.0435804 | 0.3429588 | 2.530586 | 0.0113872 | 0.0398552 |
l4
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales | 0.2819748 | 0.0889258 | 0.1076835 | 0.4562662 | 3.170900 | 0.0015197 | 0.0233017 |
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales | 0.1953538 | 0.0764693 | 0.0454767 | 0.3452308 | 2.554669 | 0.0106289 | 0.0873019 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales | 0.1990864 | 0.0908867 | 0.0209516 | 0.3772211 | 2.190489 | 0.0284888 | 0.1638107 |
l5
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales.f__bacteroidaceae | 0.1947860 | 0.0815355 | 0.0349794 | 0.3545925 | 2.388972 | 0.0168956 | 0.2092121 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae | 0.2232183 | 0.0940439 | 0.0388955 | 0.4075410 | 2.373553 | 0.0176179 | 0.2092121 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae | 0.1990864 | 0.0908867 | 0.0209516 | 0.3772211 | 2.190489 | 0.0284888 | 0.2460398 |
l6
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae.g__.eubacterium. | 0.3970460 | 0.1275892 | 0.1469758 | 0.6471162 | 3.111909 | 0.0018588 | 0.0887585 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae.g__megasphaera | 0.4000827 | 0.1416041 | 0.1225438 | 0.6776217 | 2.825361 | 0.0047227 | 0.1804084 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__clostridiaceae.g__ | 0.2425407 | 0.0943469 | 0.0576242 | 0.4274571 | 2.570734 | 0.0101483 | 0.2416618 |
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales.f__bacteroidaceae.g__bacteroides | 0.1947860 | 0.0815355 | 0.0349794 | 0.3545925 | 2.388972 | 0.0168956 | 0.2804176 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__clostridium | 0.3454360 | 0.1505929 | 0.0502793 | 0.6405927 | 2.293839 | 0.0217997 | 0.3202883 |
No Haiti data
l2
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes | 0.2585644 | 0.0699441 | 0.1214765 | 0.3956523 | 3.696729 | 0.0002184 | 0.0013104 |
| k__bacteria.p__bacteroidetes | 0.2137713 | 0.0769990 | 0.0628560 | 0.3646866 | 2.776286 | 0.0054984 | 0.0164951 |
l4
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales | 0.3197985 | 0.0708228 | 0.1809883 | 0.4586087 | 4.515471 | 0.0000063 | 0.0001200 |
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales | 0.2201357 | 0.0770481 | 0.0691242 | 0.3711471 | 2.857121 | 0.0042750 | 0.0324902 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales | 0.1839766 | 0.0915095 | 0.0046213 | 0.3633320 | 2.010465 | 0.0443820 | 0.2108145 |
l5
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales.f__bacteroidaceae | 0.2061111 | 0.0822865 | 0.0448325 | 0.3673898 | 2.504798 | 0.0122521 | 0.1347734 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae | 0.2060989 | 0.0969374 | 0.0161050 | 0.3960927 | 2.126103 | 0.0334947 | 0.2946724 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae | 0.1839766 | 0.0915095 | 0.0046213 | 0.3633320 | 2.010465 | 0.0443820 | 0.2946724 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__clostridiaceae | 0.1733438 | 0.0868412 | 0.0031382 | 0.3435495 | 1.996101 | 0.0459230 | 0.2946724 |
l6
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae.g__megasphaera | 0.4521725 | 0.1519683 | 0.1543202 | 0.7500249 | 2.975441 | 0.0029257 | 0.1062738 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae.g__.eubacterium. | 0.3594531 | 0.1297330 | 0.1051810 | 0.6137251 | 2.770714 | 0.0055934 | 0.1062738 |
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales.f__bacteroidaceae.g__bacteroides | 0.2061111 | 0.0822865 | 0.0448325 | 0.3673898 | 2.504798 | 0.0122521 | 0.1862323 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__clostridium | 0.3557799 | 0.1521514 | 0.0575687 | 0.6539911 | 2.338328 | 0.0193702 | 0.2676612 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__coprococcus | 0.5201042 | 0.2401244 | 0.0494691 | 0.9907393 | 2.165979 | 0.0303128 | 0.3839625 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__clostridiaceae.g__ | 0.5344090 | 0.2586130 | 0.0275369 | 1.0412811 | 2.066443 | 0.0387867 | 0.3877940 |
No USA(CA_MA_MO) data
l2
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__bacteroidetes | 0.2312551 | 0.0810268 | 0.0724455 | 0.3900646 | 2.854058 | 0.0043165 | 0.0250675 |
| k__bacteria.p__firmicutes | 0.2006141 | 0.0745996 | 0.0544015 | 0.3468267 | 2.689210 | 0.0071621 | 0.0250675 |
l4
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales | 0.2337644 | 0.0811408 | 0.0747312 | 0.3927975 | 2.880970 | 0.0039645 | 0.0549097 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales | 0.2968923 | 0.1099207 | 0.0814516 | 0.5123329 | 2.700967 | 0.0069138 | 0.0549097 |
| k__bacteria.p__actinobacteria.c__actinobacteria.o__actinomycetales | -0.1557879 | 0.0644216 | -0.2820518 | -0.0295239 | -2.418256 | 0.0155951 | 0.1024820 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales | 0.2117009 | 0.0993562 | 0.0169663 | 0.4064356 | 2.130727 | 0.0331117 | 0.1692374 |
| k__bacteria.p__firmicutes.c__bacilli.o__bacillales | -0.2108602 | 0.1040509 | -0.4147961 | -0.0069242 | -2.026511 | 0.0427125 | 0.1964774 |
l5
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae | 0.2996094 | 0.0741081 | 0.1543601 | 0.4448586 | 4.042869 | 0.0000528 | 0.0050161 |
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales.f__bacteroidaceae | 0.2375149 | 0.0870795 | 0.0668422 | 0.4081877 | 2.727563 | 0.0063804 | 0.0850503 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae | 0.2117009 | 0.0993562 | 0.0169663 | 0.4064356 | 2.130727 | 0.0331117 | 0.2621341 |
l6
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae.g__acidaminococcus | 2.0640609 | 0.5761745 | 0.9347797 | 3.1933421 | 3.582354 | 0.0003405 | 0.0306461 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae.g__.eubacterium. | 0.4120255 | 0.1362642 | 0.1449526 | 0.6790984 | 3.023725 | 0.0024968 | 0.1074319 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae.g__megasphaera | 0.4531996 | 0.1618768 | 0.1359269 | 0.7704723 | 2.799657 | 0.0051157 | 0.1074319 |
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales.f__bacteroidaceae.g__bacteroides | 0.2375149 | 0.0870795 | 0.0668422 | 0.4081877 | 2.727563 | 0.0063804 | 0.1074319 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae.g__veillonella | 0.2611018 | 0.1085724 | 0.0483038 | 0.4738997 | 2.404864 | 0.0161785 | 0.2080092 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__clostridium | 0.3454360 | 0.1505929 | 0.0502793 | 0.6405927 | 2.293839 | 0.0217997 | 0.2615967 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__coprococcus | 0.5470330 | 0.2571987 | 0.0429329 | 1.0511331 | 2.126889 | 0.0334293 | 0.3166986 |
Stratified analysis by birth mode for change in non-exbf vs. exbf adjusted for age
Vaginal
l2
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__proteobacteria | -0.3069577 | 0.1017253 | -0.5063356 | -0.1075798 | -3.017517 | 0.0025486 | 0.0178399 |
l4
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__proteobacteria.c__gammaproteobacteria.o__enterobacteriales | -0.2990541 | 0.1074593 | -0.5096705 | -0.0884377 | -2.782951 | 0.0053867 | 0.1158139 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales | 0.2827724 | 0.1232153 | 0.0412747 | 0.5242700 | 2.294944 | 0.0217363 | 0.2336654 |
l5
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__bacilli.o__bacillales.f__staphylococcaceae | -0.3327091 | 0.1174047 | -0.5628181 | -0.1026001 | -2.833865 | 0.0045989 | 0.1157163 |
| k__bacteria.p__proteobacteria.c__gammaproteobacteria.o__enterobacteriales.f__enterobacteriaceae | -0.2990541 | 0.1074593 | -0.5096705 | -0.0884377 | -2.782951 | 0.0053867 | 0.1157163 |
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales.f__bacteroidaceae | 0.3016820 | 0.1105580 | 0.0849923 | 0.5183717 | 2.728721 | 0.0063580 | 0.1157163 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__eubacteriaceae | 0.8045605 | 0.3139899 | 0.1891515 | 1.4199695 | 2.562377 | 0.0103958 | 0.1576704 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae | 0.2827724 | 0.1232153 | 0.0412747 | 0.5242700 | 2.294944 | 0.0217363 | 0.2197783 |
l6
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae.g__acidaminococcus | 3.3685160 | 0.4300060 | 2.5257196 | 4.2113123 | 7.833648 | 0.0000000 | 0.0000000 |
| k__bacteria.p__firmicutes.c__bacilli.o__bacillales.f__staphylococcaceae.g__staphylococcus | -0.3330596 | 0.1174105 | -0.5631799 | -0.1029393 | -2.836711 | 0.0045581 | 0.1176238 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__eubacteriaceae.g__pseudoramibacter_eubacterium | 0.8762232 | 0.3157991 | 0.2572683 | 1.4951780 | 2.774622 | 0.0055266 | 0.1176238 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__ | 0.3180415 | 0.1163513 | 0.0899972 | 0.5460858 | 2.733460 | 0.0062673 | 0.1176238 |
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales.f__bacteroidaceae.g__bacteroides | 0.3016820 | 0.1105580 | 0.0849923 | 0.5183717 | 2.728721 | 0.0063580 | 0.1176238 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae.g__.eubacterium. | 0.5384916 | 0.2026827 | 0.1412408 | 0.9357425 | 2.656820 | 0.0078881 | 0.1326643 |
| k__bacteria.p__proteobacteria.c__gammaproteobacteria.o__enterobacteriales.f__enterobacteriaceae.g__ | -0.2862286 | 0.1148106 | -0.5112532 | -0.0612040 | -2.493051 | 0.0126651 | 0.1802335 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__clostridiaceae.g__ | 0.3027671 | 0.1238937 | 0.0599398 | 0.5455944 | 2.443764 | 0.0145349 | 0.1920686 |
| k__bacteria.p__proteobacteria.c__gammaproteobacteria.o__pasteurellales.f__pasteurellaceae.g__aggregatibacter | 0.5722694 | 0.2477375 | 0.0867128 | 1.0578260 | 2.309983 | 0.0208891 | 0.2234010 |
| k__bacteria.p__firmicutes.c__bacilli.o__lactobacillales.f__streptococcaceae.g__lactococcus | 0.5835624 | 0.2676966 | 0.0588868 | 1.1082381 | 2.179940 | 0.0292619 | 0.2849187 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__blautia | 0.3639237 | 0.1848815 | 0.0015626 | 0.7262849 | 1.968416 | 0.0490202 | 0.4534368 |
C-section
l2
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__proteobacteria | -0.719666 | 0.1708821 | -1.054589 | -0.3847433 | -4.211478 | 2.54e-05 | 0.0001522 |
l4
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__proteobacteria.c__gammaproteobacteria.o__enterobacteriales | -0.5794373 | 0.2324176 | -1.034968 | -0.1239071 | -2.493087 | 0.0126638 | 0.1561867 |
l5
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__proteobacteria.c__gammaproteobacteria.o__enterobacteriales.f__enterobacteriaceae | -0.5794373 | 0.2324176 | -1.034968 | -0.1239071 | -2.493087 | 0.0126638 | 0.2596077 |
l6
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__proteobacteria.c__gammaproteobacteria.o__enterobacteriales.f__enterobacteriaceae.g__proteus | -0.2578897 | 0.0008395 | -0.2595351 | -0.2562442 | -307.189026 | 0.0000000 | 0.0000000 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__ruminococcaceae.g__anaerotruncus | -2.9244379 | 0.7060795 | -4.3083283 | -1.5405475 | -4.141797 | 0.0000345 | 0.0018723 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__veillonellaceae.g__phascolarctobacterium | -1.8840686 | 0.8567398 | -3.5632478 | -0.2048894 | -2.199114 | 0.0278698 | 0.6489685 |
| k__bacteria.p__proteobacteria.c__gammaproteobacteria.o__enterobacteriales.f__enterobacteriaceae.g__ | -0.5225859 | 0.2608359 | -1.0338148 | -0.0113570 | -2.003505 | 0.0451232 | 0.9153914 |
Meta-analysis of Trend in exbf, non-exbf and no bf adjusted for age
Phylum (l2)
Significant (pooled p<0.05) only
| estimate.conbf | se.conbf | ll.conbf | ul.conbf | z.conbf | p.conbf | p.adjust.conbf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes | 0.2891066 | 0.0810164 | 0.1303173 | 0.4478959 | 3.568494 | 0.0003590 | 0.0021542 |
| k__bacteria.p__verrucomicrobia | 0.1902821 | 0.0798894 | 0.0337017 | 0.3468625 | 2.381818 | 0.0172274 | 0.0516822 |
| k__bacteria.p__bacteroidetes | 0.2156141 | 0.0979174 | 0.0236994 | 0.4075287 | 2.201999 | 0.0276654 | 0.0553308 |
Order (l4)
Significant only
| estimate.conbf | se.conbf | ll.conbf | ul.conbf | z.conbf | p.conbf | p.adjust.conbf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales | 0.3924806 | 0.0632438 | 0.2685252 | 0.5164361 | 6.205840 | 0.0000000 | 0.0000000 |
| k__bacteria.p__actinobacteria.c__coriobacteriia.o__coriobacteriales | 0.3158688 | 0.0545196 | 0.2090123 | 0.4227252 | 5.793673 | 0.0000000 | 0.0000001 |
| k__bacteria.p__proteobacteria.c__gammaproteobacteria.o__pasteurellales | -0.2179258 | 0.0645356 | -0.3444131 | -0.0914384 | -3.376832 | 0.0007333 | 0.0045218 |
| k__bacteria.p__firmicutes.c__bacilli.o__bacillales | -0.1731560 | 0.0523488 | -0.2757578 | -0.0705541 | -3.307732 | 0.0009405 | 0.0049715 |
| k__bacteria.p__verrucomicrobia.c__verrucomicrobiae.o__verrucomicrobiales | 0.1902859 | 0.0798894 | 0.0337055 | 0.3468662 | 2.381865 | 0.0172252 | 0.0637414 |
| k__bacteria.p__bacteroidetes.c__bacteroidia.o__bacteroidales | 0.2299773 | 0.1084234 | 0.0174714 | 0.4424833 | 2.121104 | 0.0339130 | 0.0965217 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales | 0.1976105 | 0.0958110 | 0.0098243 | 0.3853966 | 2.062503 | 0.0391599 | 0.0965944 |
Family (l5)
Significant only
| estimate.conbf | se.conbf | ll.conbf | ul.conbf | z.conbf | p.conbf | p.adjust.conbf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__actinobacteria.c__coriobacteriia.o__coriobacteriales.f__coriobacteriaceae | 0.3158688 | 0.0545196 | 0.2090123 | 0.4227252 | 5.793673 | 0.0000000 | 0.0000001 |
| k__bacteria.p__proteobacteria.c__gammaproteobacteria.o__pasteurellales.f__pasteurellaceae | -0.2179258 | 0.0645356 | -0.3444131 | -0.0914384 | -3.376832 | 0.0007333 | 0.0069659 |
| k__bacteria.p__firmicutes.c__bacilli.o__bacillales.f__staphylococcaceae | -0.1841218 | 0.0598847 | -0.3014937 | -0.0667498 | -3.074603 | 0.0021078 | 0.0160195 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__peptostreptococcaceae | 0.1890903 | 0.0716934 | 0.0485738 | 0.3296068 | 2.637485 | 0.0083523 | 0.0577070 |
| k__bacteria.p__verrucomicrobia.c__verrucomicrobiae.o__verrucomicrobiales.f__verrucomicrobiaceae | 0.1902859 | 0.0798894 | 0.0337055 | 0.3468662 | 2.381865 | 0.0172252 | 0.0872855 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__ruminococcaceae | 0.2044635 | 0.0874835 | 0.0329990 | 0.3759280 | 2.337166 | 0.0194305 | 0.0922951 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__clostridiaceae | 0.1418926 | 0.0667077 | 0.0111478 | 0.2726374 | 2.127078 | 0.0334136 | 0.1233860 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae | 0.3387166 | 0.1598501 | 0.0254162 | 0.6520170 | 2.118964 | 0.0340935 | 0.1233860 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae | 0.1976105 | 0.0958110 | 0.0098243 | 0.3853966 | 2.062503 | 0.0391599 | 0.1240064 |
Genus (l6)
Significant only
| estimate.conbf | se.conbf | ll.conbf | ul.conbf | z.conbf | p.conbf | p.adjust.conbf | |
|---|---|---|---|---|---|---|---|
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__coprococcus | 0.3299376 | 0.0063390 | 0.3175133 | 0.3423619 | 52.048471 | 0.0000000 | 0.0000000 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__blautia | 0.3815612 | 0.0668433 | 0.2505508 | 0.5125716 | 5.708296 | 0.0000000 | 0.0000002 |
| k__bacteria.p__firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae.g__.eubacterium. | 0.3803923 | 0.0787618 | 0.2260221 | 0.5347626 | 4.829656 | 0.0000014 | 0.0000255 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__ | 0.3369517 | 0.0781848 | 0.1837122 | 0.4901911 | 4.309681 | 0.0000163 | 0.0002707 |
| k__bacteria.p__proteobacteria.c__gammaproteobacteria.o__pasteurellales.f__pasteurellaceae.g__haemophilus | -0.2280437 | 0.0652393 | -0.3559103 | -0.1001770 | -3.495496 | 0.0004732 | 0.0064094 |
| k__bacteria.p__firmicutes.c__bacilli.o__bacillales.f__staphylococcaceae.g__staphylococcus | -0.1829793 | 0.0594315 | -0.2994629 | -0.0664956 | -3.078824 | 0.0020782 | 0.0196292 |
| k__bacteria.p__verrucomicrobia.c__verrucomicrobiae.o__verrucomicrobiales.f__verrucomicrobiaceae.g__akkermansia | 0.1907668 | 0.0798897 | 0.0341859 | 0.3473478 | 2.387877 | 0.0169460 | 0.1166765 |
| k__bacteria.p__firmicutes.c__clostridia.o__clostridiales.f__peptostreptococcaceae.g__ | 0.2910458 | 0.1410017 | 0.0146875 | 0.5674042 | 2.064129 | 0.0390054 | 0.1823383 |
Meta-analysis of KEGG pathway relative abundance
Change in non-exbf vs. exbf
Level 2 KEGG pathway
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| Environmental.Information.Processing..Signaling.Molecules.and.Interaction | -0.0481241 | 0.0174642 | -0.0823533 | -0.0138949 | -2.755588 | 0.0058587 | 0.2167706 |
| Genetic.Information.Processing..Transcription | 0.0159785 | 0.0066440 | 0.0029565 | 0.0290005 | 2.404959 | 0.0161743 | 0.2992240 |
Nice plot
Level 3 KEGG pathway
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| Metabolism..Carbohydrate.Metabolism..Fructose.and.mannose.metabolism | 0.0748047 | 0.0153469 | 0.0447254 | 0.1048841 | 4.874259 | 0.0000011 | 0.0002436 |
| Cellular.Processes..Transport.and.Catabolism..Peroxisome | -0.0634911 | 0.0150010 | -0.0928925 | -0.0340896 | -4.232451 | 0.0000231 | 0.0025774 |
| Metabolism..Lipid.Metabolism..Fatty.acid.metabolism | -0.0862183 | 0.0256901 | -0.1365700 | -0.0358667 | -3.356095 | 0.0007905 | 0.0587615 |
| Genetic.Information.Processing..Replication.and.Repair..Base.excision.repair | 0.0170264 | 0.0054765 | 0.0062925 | 0.0277602 | 3.108958 | 0.0018775 | 0.0863346 |
| Metabolism..Carbohydrate.Metabolism..Pentose.and.glucuronate.interconversions | 0.0618250 | 0.0201180 | 0.0223944 | 0.1012557 | 3.073116 | 0.0021184 | 0.0863346 |
| Metabolism..Metabolism.of.Terpenoids.and.Polyketides..Biosynthesis.of.ansamycins | 0.0758176 | 0.0248949 | 0.0270245 | 0.1246108 | 3.045504 | 0.0023229 | 0.0863346 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Vitamin.B6.metabolism | -0.0286169 | 0.0096273 | -0.0474861 | -0.0097477 | -2.972464 | 0.0029542 | 0.0941123 |
| Metabolism..Lipid.Metabolism..Fatty.acid.biosynthesis | 0.0415976 | 0.0143916 | 0.0133905 | 0.0698047 | 2.890399 | 0.0038475 | 0.0991170 |
| Genetic.Information.Processing..Translation..Ribosome.biogenesis.in.eukaryotes | -0.0707846 | 0.0245939 | -0.1189877 | -0.0225816 | -2.878143 | 0.0040002 | 0.0991170 |
| Metabolism..Carbohydrate.Metabolism..Pentose.phosphate.pathway | 0.0339486 | 0.0122911 | 0.0098585 | 0.0580387 | 2.762045 | 0.0057441 | 0.1280925 |
| Metabolism..Metabolism.of.Other.Amino.Acids..D.Alanine.metabolism | 0.0230465 | 0.0101136 | 0.0032242 | 0.0428689 | 2.278763 | 0.0226811 | 0.4598087 |
| Unclassified..Genetic.Information.Processing..Protein.folding.and.associated.processing | -0.0110941 | 0.0050162 | -0.0209256 | -0.0012625 | -2.211653 | 0.0269906 | 0.5010248 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Drug.metabolism…other.enzymes | 0.0306056 | 0.0142804 | 0.0026166 | 0.0585946 | 2.143191 | 0.0320978 | 0.5010248 |
| Organismal.Systems..Endocrine.System..Adipocytokine.signaling.pathway | -0.1040949 | 0.0493909 | -0.2008994 | -0.0072905 | -2.107573 | 0.0350680 | 0.5010248 |
| Metabolism..Energy.Metabolism..Carbon.fixation.in.photosynthetic.organisms | 0.0263807 | 0.0125598 | 0.0017639 | 0.0509975 | 2.100403 | 0.0356934 | 0.5010248 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Drug.metabolism…cytochrome.P450 | -0.0998941 | 0.0476250 | -0.1932373 | -0.0065509 | -2.097515 | 0.0359480 | 0.5010248 |
| Human.Diseases..Infectious.Diseases..Epithelial.cell.signaling.in.Helicobacter.pylori.infection | 0.0476778 | 0.0233794 | 0.0018550 | 0.0935006 | 2.039309 | 0.0414192 | 0.5306485 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Nicotinate.and.nicotinamide.metabolism | -0.0310355 | 0.0154611 | -0.0613386 | -0.0007324 | -2.007333 | 0.0447142 | 0.5306485 |
| Metabolism..Carbohydrate.Metabolism..Amino.sugar.and.nucleotide.sugar.metabolism | 0.0289152 | 0.0146735 | 0.0001557 | 0.0576747 | 1.970575 | 0.0487726 | 0.5306485 |
Nice plot all pathways
Nice plot significant pathways only (pooled p<0.05)
Nice plot multiple testing adjusted significant pathways only (adjusted pooled p<0.1)
Sensitivity analysis
No Haiti data
Level 2
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| Organismal.Systems..Environmental.Adaptation | 0.0489196 | 0.0154245 | 0.0186881 | 0.0791511 | 3.171549 | 0.0015163 | 0.0561025 |
| Environmental.Information.Processing..Signaling.Molecules.and.Interaction | -0.0502036 | 0.0176101 | -0.0847186 | -0.0156885 | -2.850847 | 0.0043603 | 0.0806654 |
| Genetic.Information.Processing..Transcription | 0.0163666 | 0.0063851 | 0.0038521 | 0.0288811 | 2.563255 | 0.0103696 | 0.1278916 |
| Metabolism..Carbohydrate.Metabolism | 0.0131067 | 0.0066302 | 0.0001118 | 0.0261016 | 1.976820 | 0.0480620 | 0.4445737 |
Level 3
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| Metabolism..Carbohydrate.Metabolism..Fructose.and.mannose.metabolism | 0.0806811 | 0.0162836 | 0.0487659 | 0.1125964 | 4.954756 | 0.0000007 | 0.0001622 |
| Cellular.Processes..Transport.and.Catabolism..Peroxisome | -0.0650783 | 0.0150202 | -0.0945174 | -0.0356393 | -4.332715 | 0.0000147 | 0.0016496 |
| Metabolism..Lipid.Metabolism..Fatty.acid.metabolism | -0.0946530 | 0.0230876 | -0.1399040 | -0.0494021 | -4.099727 | 0.0000414 | 0.0030885 |
| Metabolism..Carbohydrate.Metabolism..Pentose.and.glucuronate.interconversions | 0.0660993 | 0.0182315 | 0.0303662 | 0.1018323 | 3.625554 | 0.0002883 | 0.0161472 |
| Metabolism..Metabolism.of.Terpenoids.and.Polyketides..Biosynthesis.of.ansamycins | 0.0880979 | 0.0249367 | 0.0392229 | 0.1369729 | 3.532866 | 0.0004111 | 0.0184164 |
| Metabolism..Carbohydrate.Metabolism..Pentose.phosphate.pathway | 0.0397027 | 0.0119850 | 0.0162125 | 0.0631929 | 3.312691 | 0.0009240 | 0.0301535 |
| Organismal.Systems..Environmental.Adaptation..Plant.pathogen.interaction | 0.0459717 | 0.0139004 | 0.0187273 | 0.0732161 | 3.307211 | 0.0009423 | 0.0301535 |
| Metabolism..Lipid.Metabolism..Fatty.acid.biosynthesis | 0.0443805 | 0.0142821 | 0.0163880 | 0.0723729 | 3.107413 | 0.0018873 | 0.0528452 |
| Organismal.Systems..Endocrine.System..Adipocytokine.signaling.pathway | -0.1279232 | 0.0422790 | -0.2107885 | -0.0450579 | -3.025693 | 0.0024806 | 0.0617403 |
| Genetic.Information.Processing..Translation..Ribosome.biogenesis.in.eukaryotes | -0.0721010 | 0.0246330 | -0.1203808 | -0.0238213 | -2.927011 | 0.0034224 | 0.0766609 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Vitamin.B6.metabolism | -0.0291619 | 0.0100993 | -0.0489563 | -0.0093676 | -2.887504 | 0.0038831 | 0.0790743 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Porphyrin.and.chlorophyll.metabolism | 0.0626417 | 0.0223883 | 0.0187615 | 0.1065219 | 2.797970 | 0.0051425 | 0.0959931 |
| Metabolism..Energy.Metabolism..Carbon.fixation.in.photosynthetic.organisms | 0.0364030 | 0.0131564 | 0.0106170 | 0.0621889 | 2.766949 | 0.0056584 | 0.0974979 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Drug.metabolism…other.enzymes | 0.0353067 | 0.0131936 | 0.0094477 | 0.0611657 | 2.676042 | 0.0074497 | 0.1191955 |
| Genetic.Information.Processing..Replication.and.Repair..Base.excision.repair | 0.0148692 | 0.0057662 | 0.0035677 | 0.0261706 | 2.578692 | 0.0099175 | 0.1481015 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Biotin.metabolism | 0.0443338 | 0.0180359 | 0.0089842 | 0.0796835 | 2.458094 | 0.0139677 | 0.1955472 |
| Unclassified..Cellular.Processes.and.Signaling..Inorganic.ion.transport.and.metabolism | -0.0854735 | 0.0363810 | -0.1567790 | -0.0141680 | -2.349397 | 0.0188039 | 0.2441364 |
| Metabolism..Lipid.Metabolism..Glycerolipid.metabolism | 0.0381790 | 0.0163608 | 0.0061125 | 0.0702456 | 2.333573 | 0.0196181 | 0.2441364 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Toluene.degradation | -0.0789239 | 0.0346447 | -0.1468262 | -0.0110215 | -2.278094 | 0.0227210 | 0.2625265 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Drug.metabolism…cytochrome.P450 | -0.1077738 | 0.0475573 | -0.2009843 | -0.0145632 | -2.266188 | 0.0234399 | 0.2625265 |
| Organismal.Systems..Endocrine.System..Insulin.signaling.pathway | 0.0604418 | 0.0275299 | 0.0064843 | 0.1143993 | 2.195500 | 0.0281278 | 0.2934589 |
| Unclassified..Genetic.Information.Processing..Protein.folding.and.associated.processing | -0.0110271 | 0.0050446 | -0.0209143 | -0.0011398 | -2.185914 | 0.0288219 | 0.2934589 |
| Metabolism..Metabolism.of.Other.Amino.Acids..D.Alanine.metabolism | 0.0214157 | 0.0100361 | 0.0017453 | 0.0410862 | 2.133866 | 0.0328537 | 0.3199669 |
| Metabolism..Amino.Acid.Metabolism..Glycine..serine.and.threonine.metabolism | -0.0151926 | 0.0072327 | -0.0293685 | -0.0010168 | -2.100542 | 0.0356812 | 0.3248701 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Nicotinate.and.nicotinamide.metabolism | -0.0326563 | 0.0156489 | -0.0633275 | -0.0019850 | -2.086812 | 0.0369051 | 0.3248701 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Metabolism.of.xenobiotics.by.cytochrome.P450 | -0.0993704 | 0.0480715 | -0.1935887 | -0.0051520 | -2.067137 | 0.0387213 | 0.3248701 |
| Genetic.Information.Processing..Translation..RNA.transport | 0.0621342 | 0.0301254 | 0.0030895 | 0.1211788 | 2.062518 | 0.0391584 | 0.3248701 |
| Metabolism..Metabolism.of.Terpenoids.and.Polyketides..Tetracycline.biosynthesis | 0.0562197 | 0.0281702 | 0.0010072 | 0.1114323 | 1.995717 | 0.0459647 | 0.3514947 |
| Genetic.Information.Processing..Folding..Sorting.and.Degradation..Proteasome | -0.0963819 | 0.0484326 | -0.1913081 | -0.0014557 | -1.990020 | 0.0465887 | 0.3514947 |
| Human.Diseases..Infectious.Diseases..Epithelial.cell.signaling.in.Helicobacter.pylori.infection | 0.0458477 | 0.0231344 | 0.0005050 | 0.0911903 | 1.981795 | 0.0475022 | 0.3514947 |
| Metabolism..Carbohydrate.Metabolism..Amino.sugar.and.nucleotide.sugar.metabolism | 0.0282869 | 0.0143465 | 0.0001683 | 0.0564055 | 1.971696 | 0.0486444 | 0.3514947 |
No USA(CA_MA_MO) data
Level 2
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| Metabolism..Glycan.Biosynthesis.and.Metabolism | 0.0519612 | 0.0115735 | 0.0292776 | 0.0746448 | 4.489673 | 0.0000071 | 0.0002639 |
| Genetic.Information.Processing..Transcription | 0.0140217 | 0.0051204 | 0.0039858 | 0.0240575 | 2.738388 | 0.0061741 | 0.1142213 |
| Environmental.Information.Processing..Signaling.Molecules.and.Interaction | -0.0463997 | 0.0186814 | -0.0830146 | -0.0097848 | -2.483737 | 0.0130012 | 0.1603479 |
Level 3
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| Metabolism..Carbohydrate.Metabolism..Fructose.and.mannose.metabolism | 0.0695846 | 0.0140831 | 0.0419821 | 0.0971870 | 4.940987 | 0.0000008 | 0.0001757 |
| Cellular.Processes..Transport.and.Catabolism..Peroxisome | -0.0593738 | 0.0158836 | -0.0905051 | -0.0282425 | -3.738054 | 0.0001854 | 0.0209558 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Xylene.degradation | -0.0564881 | 0.0187429 | -0.0932235 | -0.0197527 | -3.013838 | 0.0025797 | 0.1577341 |
| Metabolism..Lipid.Metabolism..Fatty.acid.metabolism | -0.0893386 | 0.0299073 | -0.1479559 | -0.0307213 | -2.987181 | 0.0028156 | 0.1577341 |
| Genetic.Information.Processing..Folding..Sorting.and.Degradation..Chaperones.and.folding.catalysts | 0.0242035 | 0.0083216 | 0.0078934 | 0.0405136 | 2.908510 | 0.0036316 | 0.1577341 |
| Genetic.Information.Processing..Translation..Ribosome.biogenesis.in.eukaryotes | -0.0711084 | 0.0249038 | -0.1199190 | -0.0222978 | -2.855322 | 0.0042993 | 0.1577341 |
| Metabolism..Carbohydrate.Metabolism..Pentose.and.glucuronate.interconversions | 0.0503206 | 0.0179765 | 0.0150873 | 0.0855539 | 2.799240 | 0.0051223 | 0.1577341 |
| Metabolism..Lipid.Metabolism..Fatty.acid.biosynthesis | 0.0451811 | 0.0163033 | 0.0132272 | 0.0771349 | 2.771288 | 0.0055835 | 0.1577341 |
| Metabolism..Metabolism.of.Terpenoids.and.Polyketides..Biosynthesis.of.ansamycins | 0.0717378 | 0.0274480 | 0.0179408 | 0.1255348 | 2.613593 | 0.0089596 | 0.2249850 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Vitamin.B6.metabolism | -0.0243667 | 0.0095096 | -0.0430052 | -0.0057281 | -2.562315 | 0.0103977 | 0.2302045 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Biotin.metabolism | 0.0480086 | 0.0190681 | 0.0106359 | 0.0853814 | 2.517749 | 0.0118107 | 0.2302045 |
| Metabolism..Carbohydrate.Metabolism..Pentose.phosphate.pathway | 0.0334309 | 0.0133423 | 0.0072805 | 0.0595814 | 2.505633 | 0.0122232 | 0.2302045 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Drug.metabolism…other.enzymes | 0.0381120 | 0.0159839 | 0.0067842 | 0.0694399 | 2.384403 | 0.0171069 | 0.2973962 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Chloroalkane.and.chloroalkene.degradation | -0.0440491 | 0.0187390 | -0.0807769 | -0.0073214 | -2.350670 | 0.0187396 | 0.3025111 |
| Genetic.Information.Processing..Replication.and.Repair..Base.excision.repair | 0.0136657 | 0.0059388 | 0.0020258 | 0.0253056 | 2.301070 | 0.0213877 | 0.3222407 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Drug.metabolism…cytochrome.P450 | -0.1047320 | 0.0486254 | -0.2000359 | -0.0094280 | -2.153855 | 0.0312515 | 0.4116602 |
| Environmental.Information.Processing..Signal.Transduction..Phosphatidylinositol.signaling.system | 0.0181668 | 0.0084431 | 0.0016186 | 0.0347150 | 2.151673 | 0.0314231 | 0.4116602 |
| Metabolism..Energy.Metabolism..Carbon.fixation.in.photosynthetic.organisms | 0.0344968 | 0.0161602 | 0.0028235 | 0.0661702 | 2.134681 | 0.0327871 | 0.4116602 |
| Metabolism..Metabolism.of.Other.Amino.Acids..D.Alanine.metabolism | 0.0224208 | 0.0107122 | 0.0014253 | 0.0434164 | 2.093014 | 0.0363479 | 0.4323489 |
| Genetic.Information.Processing..Folding..Sorting.and.Degradation..Proteasome | -0.1014237 | 0.0500534 | -0.1995265 | -0.0033209 | -2.026311 | 0.0427329 | 0.4828817 |
No UNC data
Level 2
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| Environmental.Information.Processing..Signaling.Molecules.and.Interaction | -0.0481241 | 0.0174642 | -0.0823533 | -0.0138949 | -2.755588 | 0.0058587 | 0.2167706 |
| Genetic.Information.Processing..Transcription | 0.0159785 | 0.0066440 | 0.0029565 | 0.0290005 | 2.404959 | 0.0161743 | 0.2992240 |
Level 3
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| Metabolism..Carbohydrate.Metabolism..Fructose.and.mannose.metabolism | 0.0748047 | 0.0153469 | 0.0447254 | 0.1048841 | 4.874259 | 0.0000011 | 0.0002468 |
| Cellular.Processes..Transport.and.Catabolism..Peroxisome | -0.0634911 | 0.0150010 | -0.0928925 | -0.0340896 | -4.232451 | 0.0000231 | 0.0026121 |
| Metabolism..Lipid.Metabolism..Fatty.acid.metabolism | -0.0862183 | 0.0256901 | -0.1365700 | -0.0358667 | -3.356095 | 0.0007905 | 0.0595520 |
| Genetic.Information.Processing..Replication.and.Repair..Base.excision.repair | 0.0170264 | 0.0054765 | 0.0062925 | 0.0277602 | 3.108958 | 0.0018775 | 0.0874960 |
| Metabolism..Carbohydrate.Metabolism..Pentose.and.glucuronate.interconversions | 0.0618250 | 0.0201180 | 0.0223944 | 0.1012557 | 3.073116 | 0.0021184 | 0.0874960 |
| Metabolism..Metabolism.of.Terpenoids.and.Polyketides..Biosynthesis.of.ansamycins | 0.0758176 | 0.0248949 | 0.0270245 | 0.1246108 | 3.045504 | 0.0023229 | 0.0874960 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Vitamin.B6.metabolism | -0.0286169 | 0.0096273 | -0.0474861 | -0.0097477 | -2.972464 | 0.0029542 | 0.0953784 |
| Metabolism..Lipid.Metabolism..Fatty.acid.biosynthesis | 0.0415976 | 0.0143916 | 0.0133905 | 0.0698047 | 2.890399 | 0.0038475 | 0.1004504 |
| Genetic.Information.Processing..Translation..Ribosome.biogenesis.in.eukaryotes | -0.0707846 | 0.0245939 | -0.1189877 | -0.0225816 | -2.878143 | 0.0040002 | 0.1004504 |
| Metabolism..Carbohydrate.Metabolism..Pentose.phosphate.pathway | 0.0339486 | 0.0122911 | 0.0098585 | 0.0580387 | 2.762045 | 0.0057441 | 0.1298157 |
| Metabolism..Metabolism.of.Other.Amino.Acids..D.Alanine.metabolism | 0.0230465 | 0.0101136 | 0.0032242 | 0.0428689 | 2.278763 | 0.0226811 | 0.4659945 |
| Unclassified..Genetic.Information.Processing..Protein.folding.and.associated.processing | -0.0110941 | 0.0050162 | -0.0209256 | -0.0012625 | -2.211653 | 0.0269906 | 0.5077651 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Drug.metabolism…other.enzymes | 0.0306056 | 0.0142804 | 0.0026166 | 0.0585946 | 2.143191 | 0.0320978 | 0.5077651 |
| Organismal.Systems..Endocrine.System..Adipocytokine.signaling.pathway | -0.1040949 | 0.0493909 | -0.2008994 | -0.0072905 | -2.107573 | 0.0350680 | 0.5077651 |
| Metabolism..Energy.Metabolism..Carbon.fixation.in.photosynthetic.organisms | 0.0263807 | 0.0125598 | 0.0017639 | 0.0509975 | 2.100403 | 0.0356934 | 0.5077651 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Drug.metabolism…cytochrome.P450 | -0.0998941 | 0.0476250 | -0.1932373 | -0.0065509 | -2.097515 | 0.0359480 | 0.5077651 |
| Human.Diseases..Infectious.Diseases..Epithelial.cell.signaling.in.Helicobacter.pylori.infection | 0.0476778 | 0.0233794 | 0.0018550 | 0.0935006 | 2.039309 | 0.0414192 | 0.5377872 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Nicotinate.and.nicotinamide.metabolism | -0.0310355 | 0.0154611 | -0.0613386 | -0.0007324 | -2.007333 | 0.0447142 | 0.5377872 |
| Metabolism..Carbohydrate.Metabolism..Amino.sugar.and.nucleotide.sugar.metabolism | 0.0289152 | 0.0146735 | 0.0001557 | 0.0576747 | 1.970575 | 0.0487726 | 0.5377872 |
stratify by birth mode
Vaginal birth
Level 2
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| Human.Diseases..Infectious.Diseases | -0.0484981 | 0.0139289 | -0.0757982 | -0.0211980 | -3.481839 | 0.0004980 | 0.0189234 |
| Human.Diseases..Neurodegenerative.Diseases | -0.0840083 | 0.0286090 | -0.1400809 | -0.0279357 | -2.936430 | 0.0033201 | 0.0630826 |
| Unclassified..Genetic.Information.Processing | -0.0202899 | 0.0083563 | -0.0366680 | -0.0039118 | -2.428091 | 0.0151785 | 0.1607306 |
| Environmental.Information.Processing..Signal.Transduction | -0.0553524 | 0.0231749 | -0.1007744 | -0.0099304 | -2.388463 | 0.0169190 | 0.1607306 |
| Metabolism..Metabolism.of.Other.Amino.Acids | -0.0167393 | 0.0076171 | -0.0316685 | -0.0018101 | -2.197602 | 0.0279775 | 0.2126291 |
Level 3 All
Significant only (pooled p<0.05)
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| Metabolism..Carbohydrate.Metabolism..Pentose.phosphate.pathway | 0.0461974 | 0.0092376 | 0.0280921 | 0.0643027 | 5.001030 | 0.0000006 | 0.0001306 |
| Metabolism..Carbohydrate.Metabolism..Propanoate.metabolism | -0.0570404 | 0.0134718 | -0.0834447 | -0.0306362 | -4.234055 | 0.0000230 | 0.0026279 |
| Metabolism..Lipid.Metabolism..Fatty.acid.metabolism | -0.0993213 | 0.0284718 | -0.1551250 | -0.0435176 | -3.488412 | 0.0004859 | 0.0370903 |
| Metabolism..Carbohydrate.Metabolism..Fructose.and.mannose.metabolism | 0.0720518 | 0.0219622 | 0.0290068 | 0.1150969 | 3.280725 | 0.0010354 | 0.0592770 |
| Unclassified..Cellular.Processes.and.Signaling..Sporulation | 0.2691131 | 0.0880246 | 0.0965881 | 0.4416381 | 3.057250 | 0.0022338 | 0.0994375 |
| Metabolism..Carbohydrate.Metabolism..Amino.sugar.and.nucleotide.sugar.metabolism | 0.0398818 | 0.0132461 | 0.0139199 | 0.0658437 | 3.010830 | 0.0026054 | 0.0994375 |
| Metabolism..Enzyme.Families..Peptidases | 0.0213727 | 0.0072551 | 0.0071530 | 0.0355924 | 2.945901 | 0.0032202 | 0.1053451 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Pantothenate.and.CoA.biosynthesis | 0.0229267 | 0.0086275 | 0.0060172 | 0.0398362 | 2.657414 | 0.0078743 | 0.2154792 |
| Metabolism..Energy.Metabolism..Carbon.fixation.in.photosynthetic.organisms | 0.0343939 | 0.0132238 | 0.0084757 | 0.0603121 | 2.600904 | 0.0092979 | 0.2154792 |
| Metabolism..Carbohydrate.Metabolism..Butanoate.metabolism | -0.0390622 | 0.0152890 | -0.0690281 | -0.0090962 | -2.554916 | 0.0106214 | 0.2154792 |
| Metabolism..Metabolism.of.Other.Amino.Acids..Glutathione.metabolism | -0.0759232 | 0.0298932 | -0.1345127 | -0.0173336 | -2.539817 | 0.0110911 | 0.2154792 |
| Metabolism..Amino.Acid.Metabolism..Tryptophan.metabolism | -0.1037075 | 0.0410760 | -0.1842150 | -0.0232001 | -2.524773 | 0.0115773 | 0.2154792 |
| Metabolism..Amino.Acid.Metabolism..Lysine.degradation | -0.0938693 | 0.0377849 | -0.1679263 | -0.0198124 | -2.484310 | 0.0129803 | 0.2154792 |
| Environmental.Information.Processing..Membrane.Transport..Bacterial.secretion.system | -0.0478536 | 0.0193032 | -0.0856872 | -0.0100200 | -2.479047 | 0.0131734 | 0.2154792 |
| Unclassified..Genetic.Information.Processing..Replication..recombination.and.repair.proteins | -0.0443230 | 0.0181120 | -0.0798220 | -0.0088241 | -2.447159 | 0.0143987 | 0.2198206 |
| Environmental.Information.Processing..Signal.Transduction..Two.component.system | -0.0610081 | 0.0262962 | -0.1125477 | -0.0094685 | -2.320034 | 0.0203390 | 0.2911026 |
| Metabolism..Carbohydrate.Metabolism..Pentose.and.glucuronate.interconversions | 0.0597831 | 0.0266534 | 0.0075434 | 0.1120228 | 2.242983 | 0.0248979 | 0.3300089 |
| Metabolism..Lipid.Metabolism..Sphingolipid.metabolism | 0.0973295 | 0.0437020 | 0.0116751 | 0.1829839 | 2.227115 | 0.0259396 | 0.3300089 |
| Metabolism..Metabolism.of.Terpenoids.and.Polyketides..Limonene.and.pinene.degradation | -0.0813978 | 0.0386717 | -0.1571928 | -0.0056027 | -2.104844 | 0.0353049 | 0.4255172 |
| Metabolism..Amino.Acid.Metabolism..Valine..leucine.and.isoleucine.degradation | -0.0895058 | 0.0434446 | -0.1746557 | -0.0043559 | -2.060227 | 0.0393768 | 0.4326503 |
| Metabolism..Energy.Metabolism..Methane.metabolism | 0.0355941 | 0.0173608 | 0.0015675 | 0.0696207 | 2.050251 | 0.0403400 | 0.4326503 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Vitamin.B6.metabolism | -0.0328569 | 0.0162180 | -0.0646435 | -0.0010703 | -2.025958 | 0.0427691 | 0.4326503 |
| Organismal.Systems..Endocrine.System..Insulin.signaling.pathway | 0.0703689 | 0.0351516 | 0.0014731 | 0.1392648 | 2.001871 | 0.0452986 | 0.4326503 |
| Environmental.Information.Processing..Membrane.Transport..Secretion.system | -0.0508999 | 0.0255435 | -0.1009642 | -0.0008357 | -1.992679 | 0.0462966 | 0.4326503 |
| Metabolism..Metabolism.of.Terpenoids.and.Polyketides..Biosynthesis.of.ansamycins | 0.0805279 | 0.0405844 | 0.0009840 | 0.1600719 | 1.984209 | 0.0472326 | 0.4326503 |
Multiple testing adjusted Significant only (adjusted pooled p<0.1)
C-section birth
Level 2
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| Human.Diseases..Infectious.Diseases | -0.1126764 | 0.0258973 | -0.1634341 | -0.0619188 | -4.350903 | 0.0000136 | 0.0005152 |
| Environmental.Information.Processing..Signal.Transduction | -0.1416460 | 0.0372818 | -0.2147171 | -0.0685750 | -3.799334 | 0.0001451 | 0.0027566 |
| Unclassified..Poorly.Characterized | -0.1803121 | 0.0692044 | -0.3159502 | -0.0446739 | -2.605500 | 0.0091740 | 0.0868309 |
| Metabolism..Energy.Metabolism | 0.0374528 | 0.0147283 | 0.0085859 | 0.0663197 | 2.542920 | 0.0109930 | 0.0868309 |
| Human.Diseases..Neurodegenerative.Diseases | -0.1436055 | 0.0567741 | -0.2548806 | -0.0323303 | -2.529420 | 0.0114251 | 0.0868309 |
| Genetic.Information.Processing..Replication.and.Repair | 0.1053877 | 0.0472699 | 0.0127404 | 0.1980350 | 2.229488 | 0.0257815 | 0.1311394 |
| Metabolism..Nucleotide.Metabolism | 0.1138804 | 0.0510945 | 0.0137370 | 0.2140238 | 2.228820 | 0.0258259 | 0.1311394 |
| Metabolism..Amino.Acid.Metabolism | 0.0256341 | 0.0117885 | 0.0025291 | 0.0487391 | 2.174502 | 0.0296674 | 0.1311394 |
| Unclassified..Cellular.Processes.and.Signaling | -0.1513433 | 0.0711795 | -0.2908525 | -0.0118341 | -2.126222 | 0.0334848 | 0.1311394 |
| Metabolism..Carbohydrate.Metabolism | 0.0257629 | 0.0121865 | 0.0018779 | 0.0496480 | 2.114057 | 0.0345104 | 0.1311394 |
Level 3 All
Significant only (pooled p<0.05)
| estimate.nebf | se.nebf | ll.nebf | ul.nebf | z.nebf | p.nebf | p.adjust.nebf | |
|---|---|---|---|---|---|---|---|
| Metabolism..Amino.Acid.Metabolism..Lysine.degradation | -0.2410428 | 0.0589751 | -0.3566318 | -0.1254538 | -4.087199 | 0.0000437 | 0.0052013 |
| Environmental.Information.Processing..Membrane.Transport..Secretion.system | -0.1668053 | 0.0409038 | -0.2469752 | -0.0866354 | -4.077994 | 0.0000454 | 0.0052013 |
| Cellular.Processes..Cell.Motility..Cytoskeleton.proteins | 0.1946407 | 0.0501812 | 0.0962873 | 0.2929941 | 3.878754 | 0.0001050 | 0.0080144 |
| Environmental.Information.Processing..Signal.Transduction..Two.component.system | -0.1563058 | 0.0417345 | -0.2381040 | -0.0745076 | -3.745237 | 0.0001802 | 0.0103178 |
| Metabolism..Amino.Acid.Metabolism..Lysine.biosynthesis | 0.0932496 | 0.0261242 | 0.0420471 | 0.1444521 | 3.569470 | 0.0003577 | 0.0147737 |
| Metabolism..Amino.Acid.Metabolism..Tryptophan.metabolism | -0.2173867 | 0.0612575 | -0.3374491 | -0.0973242 | -3.548736 | 0.0003871 | 0.0147737 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Thiamine.metabolism | 0.0778945 | 0.0227453 | 0.0333146 | 0.1224745 | 3.424647 | 0.0006156 | 0.0201389 |
| Metabolism..Lipid.Metabolism..Biosynthesis.of.unsaturated.fatty.acids | -0.1598449 | 0.0480023 | -0.2539276 | -0.0657621 | -3.329941 | 0.0008686 | 0.0248649 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Drug.metabolism…other.enzymes | 0.0699567 | 0.0212525 | 0.0283025 | 0.1116109 | 3.291685 | 0.0009959 | 0.0253399 |
| Metabolism..Lipid.Metabolism..Fatty.acid.metabolism | -0.1490154 | 0.0458870 | -0.2389524 | -0.0590784 | -3.247440 | 0.0011645 | 0.0266667 |
| Genetic.Information.Processing..Folding..Sorting.and.Degradation..Sulfur.relay.system | -0.1371891 | 0.0433387 | -0.2221315 | -0.0522467 | -3.165507 | 0.0015481 | 0.0299670 |
| Metabolism..Carbohydrate.Metabolism..Galactose.metabolism | 0.1151450 | 0.0364226 | 0.0437581 | 0.1865320 | 3.161364 | 0.0015703 | 0.0299670 |
| Genetic.Information.Processing..Replication.and.Repair..Mismatch.repair | 0.0832394 | 0.0269024 | 0.0305117 | 0.1359671 | 3.094126 | 0.0019739 | 0.0347716 |
| Metabolism..Enzyme.Families..Peptidases | 0.0367908 | 0.0120243 | 0.0132236 | 0.0603581 | 3.059696 | 0.0022156 | 0.0362412 |
| Unclassified..Cellular.Processes.and.Signaling..Inorganic.ion.transport.and.metabolism | -0.2280142 | 0.0753721 | -0.3757408 | -0.0802875 | -3.025179 | 0.0024849 | 0.0378887 |
| Metabolism..Biosynthesis.of.Other.Secondary.Metabolites..Phenylpropanoid.biosynthesis | 0.1624628 | 0.0543283 | 0.0559814 | 0.2689443 | 2.990393 | 0.0027862 | 0.0378887 |
| Genetic.Information.Processing..Replication.and.Repair..Nucleotide.excision.repair | 0.1893190 | 0.0633790 | 0.0650986 | 0.3135395 | 2.987096 | 0.0028164 | 0.0378887 |
| Metabolism..Carbohydrate.Metabolism..Amino.sugar.and.nucleotide.sugar.metabolism | 0.0854708 | 0.0289330 | 0.0287632 | 0.1421784 | 2.954096 | 0.0031359 | 0.0378887 |
| Genetic.Information.Processing..Replication.and.Repair..DNA.replication.proteins | 0.0714555 | 0.0241948 | 0.0240344 | 0.1188765 | 2.953335 | 0.0031436 | 0.0378887 |
| Unclassified..Cellular.Processes.and.Signaling..Sporulation | 0.4258710 | 0.1509691 | 0.1299770 | 0.7217649 | 2.820915 | 0.0047887 | 0.0548305 |
| Unclassified..Cellular.Processes.and.Signaling..Other.ion.coupled.transporters | -0.1077009 | 0.0387677 | -0.1836842 | -0.0317177 | -2.778113 | 0.0054676 | 0.0596224 |
| Metabolism..Amino.Acid.Metabolism..Valine..leucine.and.isoleucine.degradation | -0.1456712 | 0.0536771 | -0.2508764 | -0.0404661 | -2.713844 | 0.0066508 | 0.0666673 |
| Metabolism..Metabolism.of.Other.Amino.Acids..Glutathione.metabolism | -0.1200119 | 0.0442873 | -0.2068134 | -0.0332105 | -2.709852 | 0.0067313 | 0.0666673 |
| Metabolism..Energy.Metabolism..Carbon.fixation.in.photosynthetic.organisms | 0.0526806 | 0.0195297 | 0.0144032 | 0.0909581 | 2.697465 | 0.0069870 | 0.0666673 |
| Unclassified..Metabolism..Metabolism.of.cofactors.and.vitamins | -0.1333637 | 0.0498366 | -0.2310416 | -0.0356858 | -2.676021 | 0.0074502 | 0.0682438 |
| Human.Diseases..Infectious.Diseases..Vibrio.cholerae.pathogenic.cycle | -0.1267418 | 0.0476819 | -0.2201966 | -0.0332870 | -2.658069 | 0.0078590 | 0.0692195 |
| Metabolism..Nucleotide.Metabolism..Pyrimidine.metabolism | 0.1104510 | 0.0429456 | 0.0262793 | 0.1946228 | 2.571884 | 0.0101147 | 0.0815516 |
| Metabolism..Amino.Acid.Metabolism..Phenylalanine..tyrosine.and.tryptophan.biosynthesis | 0.0758791 | 0.0298059 | 0.0174605 | 0.1342977 | 2.545772 | 0.0109036 | 0.0815516 |
| Unclassified..Poorly.Characterized..Function.unknown | -0.1569012 | 0.0616904 | -0.2778123 | -0.0359902 | -2.543364 | 0.0109791 | 0.0815516 |
| Unclassified..Metabolism..Biosynthesis.and.biodegradation.of.secondary.metabolites | -0.2158734 | 0.0850259 | -0.3825210 | -0.0492257 | -2.538914 | 0.0111197 | 0.0815516 |
| Metabolism..Enzyme.Families..Protein.kinases | -0.1293255 | 0.0510231 | -0.2293288 | -0.0293222 | -2.534648 | 0.0112560 | 0.0815516 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..One.carbon.pool.by.folate | 0.1439633 | 0.0568953 | 0.0324506 | 0.2554761 | 2.530320 | 0.0113959 | 0.0815516 |
| Metabolism..Energy.Metabolism..Methane.metabolism | 0.0633891 | 0.0251859 | 0.0140256 | 0.1127526 | 2.516847 | 0.0118410 | 0.0821696 |
| Cellular.Processes..Cell.Growth.and.Death..Cell.cycle…Caulobacter | 0.2069000 | 0.0840125 | 0.0422384 | 0.3715616 | 2.462727 | 0.0137885 | 0.0928694 |
| Genetic.Information.Processing..Replication.and.Repair..DNA.replication | 0.0956593 | 0.0391391 | 0.0189480 | 0.1723706 | 2.444083 | 0.0145221 | 0.0950160 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Ubiquinone.and.other.terpenoid.quinone.biosynthesis | -0.1294977 | 0.0541391 | -0.2356083 | -0.0233871 | -2.391946 | 0.0167593 | 0.1066077 |
| Human.Diseases..Infectious.Diseases..Pertussis | -0.3459067 | 0.1463292 | -0.6327068 | -0.0591067 | -2.363893 | 0.0180840 | 0.1119254 |
| Metabolism..Carbohydrate.Metabolism..Starch.and.sucrose.metabolism | 0.0968519 | 0.0416485 | 0.0152222 | 0.1784815 | 2.325456 | 0.0200476 | 0.1186550 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Polycyclic.aromatic.hydrocarbon.degradation | 0.1728426 | 0.0745087 | 0.0268082 | 0.3188769 | 2.319764 | 0.0203536 | 0.1186550 |
| Metabolism..Metabolism.of.Cofactors.and.Vitamins..Pantothenate.and.CoA.biosynthesis | 0.0398297 | 0.0172203 | 0.0060784 | 0.0735810 | 2.312943 | 0.0207258 | 0.1186550 |
| Unclassified..Cellular.Processes.and.Signaling..Electron.transfer.carriers | -0.3152297 | 0.1370671 | -0.5838763 | -0.0465831 | -2.299820 | 0.0214584 | 0.1198530 |
| Cellular.Processes..Cell.Motility..Bacterial.motility.proteins | -0.1964298 | 0.0868495 | -0.3666517 | -0.0262078 | -2.261725 | 0.0237144 | 0.1292999 |
| Metabolism..Amino.Acid.Metabolism..Amino.acid.related.enzymes | 0.1029036 | 0.0459318 | 0.0128789 | 0.1929283 | 2.240355 | 0.0250679 | 0.1335010 |
| Metabolism..Glycan.Biosynthesis.and.Metabolism..Peptidoglycan.biosynthesis | 0.1655029 | 0.0742134 | 0.0200473 | 0.3109585 | 2.230095 | 0.0257412 | 0.1337390 |
| Metabolism..Glycan.Biosynthesis.and.Metabolism..Lipopolysaccharide.biosynthesis.proteins | -0.4913860 | 0.2211418 | -0.9248161 | -0.0579560 | -2.222040 | 0.0262806 | 0.1337390 |
| Unclassified..Cellular.Processes.and.Signaling..Membrane.and.intracellular.structural.molecules | -0.3249676 | 0.1470898 | -0.6132583 | -0.0366768 | -2.209314 | 0.0271528 | 0.1338000 |
| Metabolism..Energy.Metabolism..Photosynthesis | 0.3092523 | 0.1402569 | 0.0343539 | 0.5841507 | 2.204900 | 0.0274611 | 0.1338000 |
| Metabolism..Energy.Metabolism..Photosynthesis.proteins | 0.2924081 | 0.1367362 | 0.0244100 | 0.5604062 | 2.138483 | 0.0324776 | 0.1419698 |
| Genetic.Information.Processing..Replication.and.Repair..Homologous.recombination | 0.1521295 | 0.0711988 | 0.0125825 | 0.2916766 | 2.136688 | 0.0326234 | 0.1419698 |
| Genetic.Information.Processing..Folding..Sorting.and.Degradation..Protein.export | 0.2001823 | 0.0937140 | 0.0165063 | 0.3838583 | 2.136099 | 0.0326714 | 0.1419698 |
| Metabolism..Lipid.Metabolism..Sphingolipid.metabolism | 0.3160602 | 0.1483752 | 0.0252501 | 0.6068702 | 2.130141 | 0.0331600 | 0.1419698 |
| Genetic.Information.Processing..Translation..Translation.factors | 0.1979245 | 0.0932695 | 0.0151195 | 0.3807294 | 2.122070 | 0.0338319 | 0.1419698 |
| Genetic.Information.Processing..Replication.and.Repair..DNA.repair.and.recombination.proteins | 0.1416179 | 0.0668713 | 0.0105526 | 0.2726833 | 2.117768 | 0.0341947 | 0.1419698 |
| Metabolism..Metabolism.of.Terpenoids.and.Polyketides..Prenyltransferases | 0.0689059 | 0.0325922 | 0.0050264 | 0.1327855 | 2.114184 | 0.0344996 | 0.1419698 |
| Unclassified..Poorly.Characterized..General.function.prediction.only | -0.1479579 | 0.0699906 | -0.2851369 | -0.0107788 | -2.113968 | 0.0345180 | 0.1419698 |
| Unclassified..Cellular.Processes.and.Signaling..Signal.transduction.mechanisms | -0.1179107 | 0.0558385 | -0.2273522 | -0.0084693 | -2.111638 | 0.0347175 | 0.1419698 |
| Metabolism..Metabolism.of.Other.Amino.Acids..beta.Alanine.metabolism | -0.1460591 | 0.0714335 | -0.2860661 | -0.0060521 | -2.044687 | 0.0408857 | 0.1642602 |
| Metabolism..Metabolism.of.Terpenoids.and.Polyketides..Limonene.and.pinene.degradation | -0.1832241 | 0.0900308 | -0.3596813 | -0.0067669 | -2.035126 | 0.0418382 | 0.1651887 |
| Metabolism..Metabolism.of.Terpenoids.and.Polyketides..Biosynthesis.of.siderophore.group.nonribosomal.peptides | -0.2787206 | 0.1381849 | -0.5495580 | -0.0078831 | -2.017012 | 0.0436943 | 0.1690090 |
| Genetic.Information.Processing..Translation..Ribosome | 0.2622067 | 0.1303595 | 0.0067069 | 0.5177065 | 2.011413 | 0.0442818 | 0.1690090 |
| Metabolism..Xenobiotics.Biodegradation.and.Metabolism..Toluene.degradation | -0.0942549 | 0.0471773 | -0.1867207 | -0.0017891 | -1.997887 | 0.0457289 | 0.1716708 |
| Genetic.Information.Processing..Replication.and.Repair..Chromosome | 0.0281142 | 0.0141358 | 0.0004085 | 0.0558200 | 1.988861 | 0.0467165 | 0.1725498 |
| Metabolism..Carbohydrate.Metabolism..Glyoxylate.and.dicarboxylate.metabolism | -0.0952237 | 0.0482937 | -0.1898776 | -0.0005698 | -1.971762 | 0.0486368 | 0.1767908 |
Multiple testing adjusted Significant only (adjusted pooled p<0.1)
Taxa relative abundance Bangladesh data only
All analyses are adjusted for age of infants or breastfeeding status at sample collection and accounting for repeated/longitudinal sample collection.
Mean taxa relative abundance by duration of exbf in samples > 6 months
For Subramanian (Bangladesh) data only.
Duration of exbf
Change in taxa relative abundance in duration of exclusive bf >2months vs. <=2 months
Phylum (L2)
GAMLSS
| estimate | se | teststat | pval | pval.adjust | ll | ul | |
|---|---|---|---|---|---|---|---|
| firmicutes | -0.2451898 | 0.0633103 | -3.872828 | 0.0001188 | 0.0004750 | -0.3692779 | -0.1211016 |
| actinobacteria | 0.2267863 | 0.0709545 | 3.196223 | 0.0014620 | 0.0029239 | 0.0877156 | 0.3658570 |
Order (l4)
GAMLSS
| estimate | se | teststat | pval | pval.adjust | ll | ul | |
|---|---|---|---|---|---|---|---|
| actinobacteria.c__coriobacteriia.o__coriobacteriales | -0.2485089 | 0.0652555 | -3.808244 | 0.0001536 | 0.0007304 | -0.3764097 | -0.1206081 |
| firmicutes.c__bacilli.o__lactobacillales | -0.2705907 | 0.0725448 | -3.729979 | 0.0002087 | 0.0007304 | -0.4127786 | -0.1284028 |
| actinobacteria.c__actinobacteria.o__bifidobacteriales | 0.2543014 | 0.0712188 | 3.570704 | 0.0003831 | 0.0008938 | 0.1147125 | 0.3938904 |
| firmicutes.c__erysipelotrichi.o__erysipelotrichales | -0.1523709 | 0.0757899 | -2.010438 | 0.0448092 | 0.0784160 | -0.3009192 | -0.0038227 |
Family (L5)
GAMLSS
| estimate | se | teststat | pval | pval.adjust | ll | ul | |
|---|---|---|---|---|---|---|---|
| firmicutes.c__bacilli.o__lactobacillales.f__lactobacillaceae | -0.3106381 | 0.0757692 | -4.099792 | 0.0000467 | 0.0006074 | -0.4591458 | -0.1621304 |
| actinobacteria.c__coriobacteriia.o__coriobacteriales.f__coriobacteriaceae | -0.2485089 | 0.0652555 | -3.808244 | 0.0001536 | 0.0009984 | -0.3764097 | -0.1206081 |
| actinobacteria.c__actinobacteria.o__bifidobacteriales.f__bifidobacteriaceae | 0.2543014 | 0.0712188 | 3.570704 | 0.0003831 | 0.0016600 | 0.1147125 | 0.3938904 |
| bacteroidetes.c__bacteroidia.o__bacteroidales.f__prevotellaceae | -0.2684295 | 0.0800336 | -3.353959 | 0.0008441 | 0.0027434 | -0.4252954 | -0.1115636 |
| firmicutes.c__clostridia.o__clostridiales.f__clostridiaceae | -0.2173273 | 0.0799003 | -2.719980 | 0.0067053 | 0.0174337 | -0.3739319 | -0.0607226 |
| firmicutes.c__bacilli.o__lactobacillales.f__enterococcaceae | 0.1916596 | 0.0817407 | 2.344727 | 0.0193459 | 0.0419160 | 0.0314478 | 0.3518714 |
| firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae | -0.1523709 | 0.0757899 | -2.010438 | 0.0448092 | 0.0789058 | -0.3009192 | -0.0038227 |
| firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae | -0.1427715 | 0.0722439 | -1.976243 | 0.0485574 | 0.0789058 | -0.2843695 | -0.0011734 |
Genus (L6)
GAMLSS
| estimate | se | teststat | pval | pval.adjust | ll | ul | |
|---|---|---|---|---|---|---|---|
| firmicutes.c__bacilli.o__lactobacillales.f__lactobacillaceae.g__lactobacillus | -0.3315173 | 0.0755929 | -4.385561 | 0.0000135 | 0.0002844 | -0.4796795 | -0.1833552 |
| firmicutes.c__clostridia.oclostridiales.f.g__ | -0.3365252 | 0.0803138 | -4.190128 | 0.0000318 | 0.0003341 | -0.4939403 | -0.1791101 |
| actinobacteria.c__actinobacteria.o__bifidobacteriales.f__bifidobacteriaceae.g__bifidobacterium | 0.2542917 | 0.0712187 | 3.570578 | 0.0003833 | 0.0026828 | 0.1147032 | 0.3938803 |
| firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__.ruminococcus. | -0.2516784 | 0.0741715 | -3.393195 | 0.0007339 | 0.0035457 | -0.3970545 | -0.1063022 |
| bacteroidetes.c__bacteroidia.o__bacteroidales.f__prevotellaceae.g__prevotella | -0.2684274 | 0.0800336 | -3.353932 | 0.0008442 | 0.0035457 | -0.4252933 | -0.1115615 |
| actinobacteria.c__coriobacteriia.o__coriobacteriales.f__coriobacteriaceae.g__ | -0.2173260 | 0.0720564 | -3.016054 | 0.0026637 | 0.0093228 | -0.3585566 | -0.0760954 |
| firmicutes.c__clostridia.o__clostridiales.f__clostridiaceae.g__ | -0.2429816 | 0.0847773 | -2.866116 | 0.0042923 | 0.0128768 | -0.4091452 | -0.0768181 |
| firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__blautia | -0.2191360 | 0.0791422 | -2.768889 | 0.0057874 | 0.0151919 | -0.3742548 | -0.0640173 |
| actinobacteria.c__coriobacteriia.o__coriobacteriales.f__coriobacteriaceae.g__collinsella | -0.1709286 | 0.0682455 | -2.504614 | 0.0125085 | 0.0291864 | -0.3046898 | -0.0371675 |
| firmicutes.c__erysipelotrichi.o__erysipelotrichales.f__erysipelotrichaceae.g__catenibacterium | -0.2297013 | 0.0955240 | -2.404645 | 0.0164716 | 0.0345904 | -0.4169284 | -0.0424743 |
| firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__ | -0.1613206 | 0.0722253 | -2.233574 | 0.0258594 | 0.0493679 | -0.3028823 | -0.0197590 |
| firmicutes.c__bacilli.o__lactobacillales.f__enterococcaceae.g__enterococcus | 0.1801273 | 0.0833351 | 2.161482 | 0.0310272 | 0.0542975 | 0.0167905 | 0.3434641 |
Modification effect of breastfeeding status on samples of patients with vs. without diarrhea at sample collection
Subramania (Bangladesh) data only.
Taxa relative abundance in samples of patients with vs. without diarrhea at sample collection
Only LME was used as GAMLSS has issues with small sample size (when stratifying). LME as showed above has lower power than GAMLSS in general.
After 6 month
Stratified by duration of exclusive bf
Family
GAMLSS
In infants with duration of exclusive bf <=2 months
| estimate | se | teststat | pval | pval.adjust | ll | ul | |
|---|---|---|---|---|---|---|---|
| actinobacteria.c__actinobacteria.o__bifidobacteriales.f__bifidobacteriaceae | -0.7714898 | 0.1993835 | -3.869376 | 0.0001287 | 0.0016732 | -1.1622815 | -0.3806981 |
| actinobacteria.c__coriobacteriia.o__coriobacteriales.f__coriobacteriaceae | -0.6912195 | 0.1960537 | -3.525664 | 0.0004749 | 0.0030865 | -1.0754847 | -0.3069543 |
| firmicutes.c__bacilli.o__lactobacillales.f__streptococcaceae | 0.5260925 | 0.1836007 | 2.865417 | 0.0043999 | 0.0190660 | 0.1662351 | 0.8859498 |
In infants with duration of exclusive bf >2 months
estimate se teststat pval pval.adjust ll ul ——— — ——— —– ———— — —
Genus
GAMLSS
In infants with duration of exclusive bf <=2 months
| estimate | se | teststat | pval | pval.adjust | ll | ul | |
|---|---|---|---|---|---|---|---|
| actinobacteria.c__actinobacteria.o__bifidobacteriales.f__bifidobacteriaceae.g__bifidobacterium | -0.7714809 | 0.1993838 | -3.869325 | 0.0001287 | 0.0027034 | -1.1622732 | -0.3806886 |
| firmicutes.c__bacilli.o__lactobacillales.f__streptococcaceae.g__streptococcus | 0.5243671 | 0.1841506 | 2.847491 | 0.0046498 | 0.0488224 | 0.1634320 | 0.8853023 |
| actinobacteria.c__coriobacteriia.o__coriobacteriales.f__coriobacteriaceae.g__collinsella | -0.4992648 | 0.2105904 | -2.370786 | 0.0182565 | 0.1237102 | -0.9120220 | -0.0865075 |
| actinobacteria.c__coriobacteriia.o__coriobacteriales.f__coriobacteriaceae.g__ | -0.4975598 | 0.2188542 | -2.273476 | 0.0235638 | 0.1237102 | -0.9265141 | -0.0686055 |
In infants with duration of exclusive bf >2 months
| estimate | se | teststat | pval | pval.adjust | ll | ul | |
|---|---|---|---|---|---|---|---|
| firmicutes.c__clostridia.o__clostridiales.f__lachnospiraceae.g__ | 0.3859128 | 0.2285308 | 1.688668 | 0.0923469 | 0.9809468 | -0.0620076 | 0.8338332 |
Stratified by bf status
Family
GAMLSS
In non-exclusive bf infants
| estimate | se | teststat | pval | pval.adjust | ll | ul | |
|---|---|---|---|---|---|---|---|
| actinobacteria.c__coriobacteriia.o__coriobacteriales.f__coriobacteriaceae | -0.3440389 | 0.1461708 | -2.353678 | 0.0189040 | 0.2457518 | -0.6305337 | -0.0575442 |
| actinobacteria.c__actinobacteria.o__bifidobacteriales.f__bifidobacteriaceae | -0.2512789 | 0.1516653 | -1.656799 | 0.0980727 | 0.4727405 | -0.5485430 | 0.0459851 |
In no bf infants
| estimate | se | teststat | pval | pval.adjust | ll | ul | |
|---|---|---|---|---|---|---|---|
| firmicutes.c__bacilli.o__lactobacillales.f__streptococcaceae | 2.090855 | 0.6246379 | 3.347308 | 0.0017567 | 0.0228374 | 0.8665651 | 3.3151455 |
| actinobacteria.c__actinobacteria.o__bifidobacteriales.f__bifidobacteriaceae | -1.840426 | 0.7653211 | -2.404776 | 0.0207821 | 0.1350835 | -3.3404553 | -0.3403967 |
Genus
GAMLSS
In bf infants
| estimate | se | teststat | pval | pval.adjust | ll | ul | |
|---|---|---|---|---|---|---|---|
| actinobacteria.c__coriobacteriia.o__coriobacteriales.f__coriobacteriaceae.g__collinsella | -0.2910103 | 0.1480753 | -1.965286 | 0.0498330 | 0.654706 | -0.5812379 | -0.0007827 |
| actinobacteria.c__actinobacteria.o__bifidobacteriales.f__bifidobacteriaceae.g__bifidobacterium | -0.2512877 | 0.1516657 | -1.656853 | 0.0980617 | 0.654706 | -0.5485524 | 0.0459770 |
In non-bf infants
| estimate | se | teststat | pval | pval.adjust | ll | ul | |
|---|---|---|---|---|---|---|---|
| firmicutes.c__bacilli.o__lactobacillales.f__streptococcaceae.g__streptococcus | 2.085766 | 0.6249206 | 3.337650 | 0.0018053 | 0.0379113 | 0.8609218 | 3.3106107 |
| actinobacteria.c__actinobacteria.o__bifidobacteriales.f__bifidobacteriaceae.g__bifidobacterium | -1.840411 | 0.7653209 | -2.404758 | 0.0207830 | 0.2182216 | -3.3404403 | -0.3403824 |
Microbiome age in samples of infants with vs. without diarrhea at sample collection stratified by duration of exclusive breastfeeding
With GAMM fit and 95%CI.
GAM part
| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | 10.3788398 | 0.2835665 | 36.6010753 | 0.0000000 |
| dia.exbf2No.>2 months | -1.1507899 | 0.4879123 | -2.3585999 | 0.0186104 |
| dia.exbf2Yes.<=2 months | -1.1945958 | 0.4839537 | -2.4684094 | 0.0138028 |
| dia.exbf2Yes.>2 months | -0.5097696 | 0.8117265 | -0.6280066 | 0.5301988 |
| edf | Ref.df | F | p-value | |
|---|---|---|---|---|
| s(age.sample):dia.exbf2No.<=2 months | 5.032806 | 5.032806 | 251.05395 | 0 |
| s(age.sample):dia.exbf2No.>2 months | 4.191756 | 4.191756 | 149.07931 | 0 |
| s(age.sample):dia.exbf2Yes.<=2 months | 1.000000 | 1.000000 | 37.58735 | 0 |
| s(age.sample):dia.exbf2Yes.>2 months | 1.000000 | 1.000000 | 49.79342 | 0 |
LME part
| Value | Std.Error | DF | t-value | p-value | |
|---|---|---|---|---|---|
| X(Intercept) | 10.3788398 | 0.2843456 | 689 | 36.500798 | 0.0000000 |
| Xdia.exbf2No.>2 months | -1.1507899 | 0.4892527 | 689 | -2.352138 | 0.0189463 |
| Xdia.exbf2Yes.<=2 months | -1.1945958 | 0.4852832 | 689 | -2.461647 | 0.0140740 |
| Xdia.exbf2Yes.>2 months | -0.5097696 | 0.8139565 | 689 | -0.626286 | 0.5313348 |
| Xs(age.sample):dia.exbf2No.<=2 monthsFx1 | 1.8308388 | 1.3486999 | 689 | 1.357484 | 0.1750718 |
| Xs(age.sample):dia.exbf2No.>2 monthsFx1 | 1.6657329 | 1.3242074 | 689 | 1.257909 | 0.2088507 |
| Xs(age.sample):dia.exbf2Yes.<=2 monthsFx1 | 3.4720580 | 0.5678815 | 689 | 6.114054 | 0.0000000 |
| Xs(age.sample):dia.exbf2Yes.>2 monthsFx1 | 5.0913209 | 0.7234958 | 689 | 7.037112 | 0.0000000 |
Test for heterogeneity (interaction)
| Estimate | Std. Error | t value | p.val | |
|---|---|---|---|---|
| (Intercept) | 3.7678265 | 0.3316981 | 11.359203 | 0.0000000 |
| age.sample | 0.6832422 | 0.0173814 | 39.308910 | 0.0000000 |
| month.exbf2>2 months | -1.2353814 | 0.5064509 | -2.439291 | 0.0147161 |
| diarrheaYes | -1.0072569 | 0.5024243 | -2.004793 | 0.0449851 |
| month.exbf2>2 months:diarrheaYes | 1.8143024 | 0.9006571 | 2.014421 | 0.0439654 |
Alpha diversity in samples of infants with vs. without diarrhea at sample collection stratified by duration of exclusive breastfeeding
With GAMM fit and 95%CI.
Shannon
| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | 3.0665206 | 0.0823202 | 37.2511259 | 0.0000000 |
| dia.exbf2No.>2 months | -0.1567257 | 0.1292484 | -1.2125925 | 0.2255782 |
| dia.exbf2Yes.<=2 months | -0.5837970 | 0.1257959 | -4.6408273 | 0.0000039 |
| dia.exbf2Yes.>2 months | -0.0919724 | 0.1901039 | -0.4838004 | 0.6286357 |
| edf | Ref.df | F | p-value | |
|---|---|---|---|---|
| s(age.sample):dia.exbf2No.<=2 months | 1.000000 | 1.000000 | 511.09021 | 0.00e+00 |
| s(age.sample):dia.exbf2No.>2 months | 5.974811 | 5.974811 | 75.05942 | 0.00e+00 |
| s(age.sample):dia.exbf2Yes.<=2 months | 1.000000 | 1.000000 | 15.96302 | 6.93e-05 |
| s(age.sample):dia.exbf2Yes.>2 months | 1.000000 | 1.000000 | 43.95975 | 0.00e+00 |
| Value | Std.Error | DF | t-value | p-value | |
|---|---|---|---|---|---|
| X(Intercept) | 3.0665206 | 0.0824874 | 935 | 37.175641 | 0.0000000 |
| Xdia.exbf2No.>2 months | -0.1567257 | 0.1295109 | 935 | -1.210135 | 0.2265328 |
| Xdia.exbf2Yes.<=2 months | -0.5837970 | 0.1260513 | 935 | -4.631425 | 0.0000041 |
| Xdia.exbf2Yes.>2 months | -0.0919724 | 0.1904900 | 935 | -0.482820 | 0.6293366 |
| Xs(age.sample):dia.exbf2No.<=2 monthsFx1 | 0.8428954 | 0.0373599 | 935 | 22.561490 | 0.0000000 |
| Xs(age.sample):dia.exbf2No.>2 monthsFx1 | -0.7155803 | 0.5005884 | 935 | -1.429479 | 0.1532008 |
| Xs(age.sample):dia.exbf2Yes.<=2 monthsFx1 | 0.5554706 | 0.1393107 | 935 | 3.987278 | 0.0000720 |
| Xs(age.sample):dia.exbf2Yes.>2 monthsFx1 | 0.9760833 | 0.1475164 | 935 | 6.616780 | 0.0000000 |
GAM part
| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | 3.0665206 | 0.0823202 | 37.2511259 | 0.0000000 |
| dia.exbf2No.>2 months | -0.1567257 | 0.1292484 | -1.2125925 | 0.2255782 |
| dia.exbf2Yes.<=2 months | -0.5837970 | 0.1257959 | -4.6408273 | 0.0000039 |
| dia.exbf2Yes.>2 months | -0.0919724 | 0.1901039 | -0.4838004 | 0.6286357 |
| edf | Ref.df | F | p-value | |
|---|---|---|---|---|
| s(age.sample):dia.exbf2No.<=2 months | 1.000000 | 1.000000 | 511.09021 | 0.00e+00 |
| s(age.sample):dia.exbf2No.>2 months | 5.974811 | 5.974811 | 75.05942 | 0.00e+00 |
| s(age.sample):dia.exbf2Yes.<=2 months | 1.000000 | 1.000000 | 15.96302 | 6.93e-05 |
| s(age.sample):dia.exbf2Yes.>2 months | 1.000000 | 1.000000 | 43.95975 | 0.00e+00 |
LME part
| Value | Std.Error | DF | t-value | p-value | |
|---|---|---|---|---|---|
| X(Intercept) | 3.0665206 | 0.0824874 | 935 | 37.175641 | 0.0000000 |
| Xdia.exbf2No.>2 months | -0.1567257 | 0.1295109 | 935 | -1.210135 | 0.2265328 |
| Xdia.exbf2Yes.<=2 months | -0.5837970 | 0.1260513 | 935 | -4.631425 | 0.0000041 |
| Xdia.exbf2Yes.>2 months | -0.0919724 | 0.1904900 | 935 | -0.482820 | 0.6293366 |
| Xs(age.sample):dia.exbf2No.<=2 monthsFx1 | 0.8428954 | 0.0373599 | 935 | 22.561490 | 0.0000000 |
| Xs(age.sample):dia.exbf2No.>2 monthsFx1 | -0.7155803 | 0.5005884 | 935 | -1.429479 | 0.1532008 |
| Xs(age.sample):dia.exbf2Yes.<=2 monthsFx1 | 0.5554706 | 0.1393107 | 935 | 3.987278 | 0.0000720 |
| Xs(age.sample):dia.exbf2Yes.>2 monthsFx1 | 0.9760833 | 0.1475164 | 935 | 6.616780 | 0.0000000 |
Test for heterogeneity (interaction)
| Estimate | Std. Error | t value | p.val | |
|---|---|---|---|---|
| (Intercept) | 1.8029966 | 0.0917394 | 19.653450 | 0.0000000 |
| age.sample | 0.1228124 | 0.0040692 | 30.181133 | 0.0000000 |
| month.exbf2>2 months | -0.1604039 | 0.1316082 | -1.218798 | 0.2229207 |
| diarrheaYes | -0.5210706 | 0.1247534 | -4.176806 | 0.0000296 |
| month.exbf2>2 months:diarrheaYes | 0.5706337 | 0.1973949 | 2.890823 | 0.0038423 |
Observed_species
| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | 151.196675 | 8.778134 | 17.2242389 | 0.0000000 |
| dia.exbf2No.>2 months | 6.376610 | 13.831570 | 0.4610185 | 0.6448877 |
| dia.exbf2Yes.<=2 months | -32.741233 | 8.978024 | -3.6468195 | 0.0002795 |
| dia.exbf2Yes.>2 months | 8.288239 | 17.024836 | 0.4868322 | 0.6264862 |
| edf | Ref.df | F | p-value | |
|---|---|---|---|---|
| s(age.sample):dia.exbf2No.<=2 months | 2.241236 | 2.241236 | 186.022933 | 0.0000000 |
| s(age.sample):dia.exbf2No.>2 months | 4.803475 | 4.803475 | 86.288380 | 0.0000000 |
| s(age.sample):dia.exbf2Yes.<=2 months | 1.000000 | 1.000000 | 9.841034 | 0.0017564 |
| s(age.sample):dia.exbf2Yes.>2 months | 1.000000 | 1.000000 | 34.546738 | 0.0000000 |
| Value | Std.Error | DF | t-value | p-value | |
|---|---|---|---|---|---|
| X(Intercept) | 151.196675 | 8.795958 | 935 | 17.1893366 | 0.0000000 |
| Xdia.exbf2No.>2 months | 6.376610 | 13.859654 | 935 | 0.4600843 | 0.6455627 |
| Xdia.exbf2Yes.<=2 months | -32.741233 | 8.996254 | 935 | -3.6394298 | 0.0002882 |
| Xdia.exbf2Yes.>2 months | 8.288239 | 17.059405 | 935 | 0.4858457 | 0.6271904 |
| Xs(age.sample):dia.exbf2No.<=2 monthsFx1 | 51.801469 | 8.730802 | 935 | 5.9331857 | 0.0000000 |
| Xs(age.sample):dia.exbf2No.>2 monthsFx1 | -19.877541 | 26.849174 | 935 | -0.7403409 | 0.4592790 |
| Xs(age.sample):dia.exbf2Yes.<=2 monthsFx1 | 31.121465 | 9.940785 | 935 | 3.1306850 | 0.0017981 |
| Xs(age.sample):dia.exbf2Yes.>2 monthsFx1 | 61.612841 | 10.503858 | 935 | 5.8657345 | 0.0000000 |
GAM part
| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | 151.196675 | 8.778134 | 17.2242389 | 0.0000000 |
| dia.exbf2No.>2 months | 6.376610 | 13.831570 | 0.4610185 | 0.6448877 |
| dia.exbf2Yes.<=2 months | -32.741233 | 8.978024 | -3.6468195 | 0.0002795 |
| dia.exbf2Yes.>2 months | 8.288239 | 17.024836 | 0.4868322 | 0.6264862 |
| edf | Ref.df | F | p-value | |
|---|---|---|---|---|
| s(age.sample):dia.exbf2No.<=2 months | 2.241236 | 2.241236 | 186.022933 | 0.0000000 |
| s(age.sample):dia.exbf2No.>2 months | 4.803475 | 4.803475 | 86.288380 | 0.0000000 |
| s(age.sample):dia.exbf2Yes.<=2 months | 1.000000 | 1.000000 | 9.841034 | 0.0017564 |
| s(age.sample):dia.exbf2Yes.>2 months | 1.000000 | 1.000000 | 34.546738 | 0.0000000 |
LME part
| Value | Std.Error | DF | t-value | p-value | |
|---|---|---|---|---|---|
| X(Intercept) | 151.196675 | 8.795958 | 935 | 17.1893366 | 0.0000000 |
| Xdia.exbf2No.>2 months | 6.376610 | 13.859654 | 935 | 0.4600843 | 0.6455627 |
| Xdia.exbf2Yes.<=2 months | -32.741233 | 8.996254 | 935 | -3.6394298 | 0.0002882 |
| Xdia.exbf2Yes.>2 months | 8.288239 | 17.059405 | 935 | 0.4858457 | 0.6271904 |
| Xs(age.sample):dia.exbf2No.<=2 monthsFx1 | 51.801469 | 8.730802 | 935 | 5.9331857 | 0.0000000 |
| Xs(age.sample):dia.exbf2No.>2 monthsFx1 | -19.877541 | 26.849174 | 935 | -0.7403409 | 0.4592790 |
| Xs(age.sample):dia.exbf2Yes.<=2 monthsFx1 | 31.121465 | 9.940785 | 935 | 3.1306850 | 0.0017981 |
| Xs(age.sample):dia.exbf2Yes.>2 monthsFx1 | 61.612841 | 10.503858 | 935 | 5.8657345 | 0.0000000 |
Test for heterogeneity (interaction)
| Estimate | Std. Error | t value | p.val | |
|---|---|---|---|---|
| (Intercept) | 67.218370 | 9.3632479 | 7.1789587 | 0.0000000 |
| age.sample | 8.165080 | 0.2895546 | 28.1987576 | 0.0000000 |
| month.exbf2>2 months | 6.548791 | 14.1631117 | 0.4623836 | 0.6438062 |
| diarrheaYes | -27.156839 | 8.8730060 | -3.0606132 | 0.0022088 |
| month.exbf2>2 months:diarrheaYes | 28.115237 | 14.0092249 | 2.0069088 | 0.0447594 |
Pd_whole_tree
| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | 11.1473183 | 0.4242502 | 26.2753392 | 0.0000000 |
| dia.exbf2No.>2 months | 0.2157323 | 0.6676390 | 0.3231271 | 0.7466679 |
| dia.exbf2Yes.<=2 months | -2.4295713 | 0.5177632 | -4.6924371 | 0.0000031 |
| dia.exbf2Yes.>2 months | -0.1330212 | 0.8797770 | -0.1511987 | 0.8798500 |
| edf | Ref.df | F | p-value | |
|---|---|---|---|---|
| s(age.sample):dia.exbf2No.<=2 months | 1.00000 | 1.00000 | 651.06494 | 0.0e+00 |
| s(age.sample):dia.exbf2No.>2 months | 4.26171 | 4.26171 | 146.66378 | 0.0e+00 |
| s(age.sample):dia.exbf2Yes.<=2 months | 1.00000 | 1.00000 | 20.80080 | 5.7e-06 |
| s(age.sample):dia.exbf2Yes.>2 months | 1.00000 | 1.00000 | 48.09244 | 0.0e+00 |
| Value | Std.Error | DF | t-value | p-value | |
|---|---|---|---|---|---|
| X(Intercept) | 11.1473183 | 0.4251117 | 935 | 26.2220945 | 0.0000000 |
| Xdia.exbf2No.>2 months | 0.2157323 | 0.6689947 | 935 | 0.3224723 | 0.7471670 |
| Xdia.exbf2Yes.<=2 months | -2.4295713 | 0.5188143 | 935 | -4.6829302 | 0.0000032 |
| Xdia.exbf2Yes.>2 months | -0.1330212 | 0.8815636 | 935 | -0.1508923 | 0.8800932 |
| Xs(age.sample):dia.exbf2No.<=2 monthsFx1 | 3.9257946 | 0.1541688 | 935 | 25.4642659 | 0.0000000 |
| Xs(age.sample):dia.exbf2No.>2 monthsFx1 | 0.5241955 | 1.3248785 | 935 | 0.3956555 | 0.6924494 |
| Xs(age.sample):dia.exbf2Yes.<=2 monthsFx1 | 2.6094784 | 0.5733168 | 935 | 4.5515473 | 0.0000060 |
| Xs(age.sample):dia.exbf2Yes.>2 monthsFx1 | 4.1958246 | 0.6062613 | 935 | 6.9208183 | 0.0000000 |
GAM part
| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | 11.1473183 | 0.4242502 | 26.2753392 | 0.0000000 |
| dia.exbf2No.>2 months | 0.2157323 | 0.6676390 | 0.3231271 | 0.7466679 |
| dia.exbf2Yes.<=2 months | -2.4295713 | 0.5177632 | -4.6924371 | 0.0000031 |
| dia.exbf2Yes.>2 months | -0.1330212 | 0.8797770 | -0.1511987 | 0.8798500 |
| edf | Ref.df | F | p-value | |
|---|---|---|---|---|
| s(age.sample):dia.exbf2No.<=2 months | 1.00000 | 1.00000 | 651.06494 | 0.0e+00 |
| s(age.sample):dia.exbf2No.>2 months | 4.26171 | 4.26171 | 146.66378 | 0.0e+00 |
| s(age.sample):dia.exbf2Yes.<=2 months | 1.00000 | 1.00000 | 20.80080 | 5.7e-06 |
| s(age.sample):dia.exbf2Yes.>2 months | 1.00000 | 1.00000 | 48.09244 | 0.0e+00 |
LME part
| Value | Std.Error | DF | t-value | p-value | |
|---|---|---|---|---|---|
| X(Intercept) | 11.1473183 | 0.4251117 | 935 | 26.2220945 | 0.0000000 |
| Xdia.exbf2No.>2 months | 0.2157323 | 0.6689947 | 935 | 0.3224723 | 0.7471670 |
| Xdia.exbf2Yes.<=2 months | -2.4295713 | 0.5188143 | 935 | -4.6829302 | 0.0000032 |
| Xdia.exbf2Yes.>2 months | -0.1330212 | 0.8815636 | 935 | -0.1508923 | 0.8800932 |
| Xs(age.sample):dia.exbf2No.<=2 monthsFx1 | 3.9257946 | 0.1541688 | 935 | 25.4642659 | 0.0000000 |
| Xs(age.sample):dia.exbf2No.>2 monthsFx1 | 0.5241955 | 1.3248785 | 935 | 0.3956555 | 0.6924494 |
| Xs(age.sample):dia.exbf2Yes.<=2 monthsFx1 | 2.6094784 | 0.5733168 | 935 | 4.5515473 | 0.0000060 |
| Xs(age.sample):dia.exbf2Yes.>2 monthsFx1 | 4.1958246 | 0.6062613 | 935 | 6.9208183 | 0.0000000 |
Test for heterogeneity (interaction)
| Estimate | Std. Error | t value | p.val | |
|---|---|---|---|---|
| (Intercept) | 5.1010594 | 0.4591138 | 11.1106653 | 0.0000000 |
| age.sample | 0.5894225 | 0.0166254 | 35.4531752 | 0.0000000 |
| month.exbf2>2 months | 0.2033228 | 0.6822247 | 0.2980291 | 0.7656809 |
| diarrheaYes | -2.1261538 | 0.5095509 | -4.1726032 | 0.0000301 |
| month.exbf2>2 months:diarrheaYes | 1.7538795 | 0.8050786 | 2.1785195 | 0.0293674 |
Chao1
| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | 367.19115 | 24.93875 | 14.7237215 | 0.0000000 |
| dia.exbf2No.>2 months | 16.36035 | 39.31689 | 0.4161151 | 0.6774169 |
| dia.exbf2Yes.<=2 months | -86.62794 | 23.43335 | -3.6967801 | 0.0002305 |
| dia.exbf2Yes.>2 months | 28.78746 | 47.08230 | 0.6114285 | 0.5410577 |
| edf | Ref.df | F | p-value | |
|---|---|---|---|---|
| s(age.sample):dia.exbf2No.<=2 months | 1.502023 | 1.502023 | 261.413376 | 0.0000000 |
| s(age.sample):dia.exbf2No.>2 months | 4.677640 | 4.677640 | 76.504447 | 0.0000000 |
| s(age.sample):dia.exbf2Yes.<=2 months | 1.000000 | 1.000000 | 7.810505 | 0.0052936 |
| s(age.sample):dia.exbf2Yes.>2 months | 1.000000 | 1.000000 | 29.909461 | 0.0000001 |
| Value | Std.Error | DF | t-value | p-value | |
|---|---|---|---|---|---|
| X(Intercept) | 367.19115 | 24.98938 | 935 | 14.6938872 | 0.0000000 |
| Xdia.exbf2No.>2 months | 16.36035 | 39.39672 | 935 | 0.4152720 | 0.6780381 |
| Xdia.exbf2Yes.<=2 months | -86.62794 | 23.48093 | 935 | -3.6892894 | 0.0002379 |
| Xdia.exbf2Yes.>2 months | 28.78746 | 47.17789 | 935 | 0.6101897 | 0.5418844 |
| Xs(age.sample):dia.exbf2No.<=2 monthsFx1 | 134.05173 | 12.55943 | 935 | 10.6733923 | 0.0000000 |
| Xs(age.sample):dia.exbf2No.>2 monthsFx1 | -43.96611 | 67.65832 | 935 | -0.6498257 | 0.5159644 |
| Xs(age.sample):dia.exbf2Yes.<=2 monthsFx1 | 72.36395 | 25.94559 | 935 | 2.7890649 | 0.0053934 |
| Xs(age.sample):dia.exbf2Yes.>2 monthsFx1 | 149.59600 | 27.40922 | 935 | 5.4578722 | 0.0000001 |
GAM part
| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | 367.19115 | 24.93875 | 14.7237215 | 0.0000000 |
| dia.exbf2No.>2 months | 16.36035 | 39.31689 | 0.4161151 | 0.6774169 |
| dia.exbf2Yes.<=2 months | -86.62794 | 23.43335 | -3.6967801 | 0.0002305 |
| dia.exbf2Yes.>2 months | 28.78746 | 47.08230 | 0.6114285 | 0.5410577 |
| edf | Ref.df | F | p-value | |
|---|---|---|---|---|
| s(age.sample):dia.exbf2No.<=2 months | 1.502023 | 1.502023 | 261.413376 | 0.0000000 |
| s(age.sample):dia.exbf2No.>2 months | 4.677640 | 4.677640 | 76.504447 | 0.0000000 |
| s(age.sample):dia.exbf2Yes.<=2 months | 1.000000 | 1.000000 | 7.810505 | 0.0052936 |
| s(age.sample):dia.exbf2Yes.>2 months | 1.000000 | 1.000000 | 29.909461 | 0.0000001 |
LME part
| Value | Std.Error | DF | t-value | p-value | |
|---|---|---|---|---|---|
| X(Intercept) | 367.19115 | 24.98938 | 935 | 14.6938872 | 0.0000000 |
| Xdia.exbf2No.>2 months | 16.36035 | 39.39672 | 935 | 0.4152720 | 0.6780381 |
| Xdia.exbf2Yes.<=2 months | -86.62794 | 23.48093 | 935 | -3.6892894 | 0.0002379 |
| Xdia.exbf2Yes.>2 months | 28.78746 | 47.17789 | 935 | 0.6101897 | 0.5418844 |
| Xs(age.sample):dia.exbf2No.<=2 monthsFx1 | 134.05173 | 12.55943 | 935 | 10.6733923 | 0.0000000 |
| Xs(age.sample):dia.exbf2No.>2 monthsFx1 | -43.96611 | 67.65832 | 935 | -0.6498257 | 0.5159644 |
| Xs(age.sample):dia.exbf2Yes.<=2 monthsFx1 | 72.36395 | 25.94559 | 935 | 2.7890649 | 0.0053934 |
| Xs(age.sample):dia.exbf2Yes.>2 monthsFx1 | 149.59600 | 27.40922 | 935 | 5.4578722 | 0.0000001 |
Test for heterogeneity (interaction)
| Estimate | Std. Error | t value | p.val | |
|---|---|---|---|---|
| (Intercept) | 161.48642 | 26.4705453 | 6.1006078 | 0.0000000 |
| age.sample | 20.00874 | 0.7538543 | 26.5419213 | 0.0000000 |
| month.exbf2>2 months | 16.28471 | 40.3235504 | 0.4038512 | 0.6863222 |
| diarrheaYes | -72.27871 | 23.0991493 | -3.1290636 | 0.0017536 |
| month.exbf2>2 months:diarrheaYes | 83.14805 | 36.4602574 | 2.2805118 | 0.0225774 |
Combined graph
R session information
R version 3.4.2 (2017-09-28)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] gplots_3.0.1 bindrcpp_0.2 meta_4.9-0
[4] randomForest_4.6-12 gdata_2.18.0 scales_0.5.0
[7] RColorBrewer_1.1-2 geepack_1.2-1 zoo_1.8-0
[10] itsadug_2.3 plotfunctions_1.3 mgcv_1.8-22
[13] nlme_3.1-131 reshape2_1.4.3 lmerTest_2.0-36
[16] sjPlot_2.4.0 sjmisc_2.6.3 lme4_1.1-15
[19] Matrix_1.2-12 tidyr_0.7.2 dtplyr_0.0.2
[22] data.table_1.10.4-3 dplyr_0.7.4 date_1.2-37
[25] lubridate_1.7.1 chron_2.3-51 gmodels_2.16.2
[28] gridExtra_2.3 plyr_1.8.4 digest_0.6.12
[31] caret_6.0-78 ggplot2_2.2.1 lattice_0.20-35
[34] knitr_1.17
loaded via a namespace (and not attached):
[1] backports_1.1.1 Hmisc_4.0-3 blme_1.0-4
[4] lazyeval_0.2.1 TMB_1.7.11 splines_3.4.2
[7] TH.data_1.0-8 foreach_1.4.3 htmltools_0.3.6
[10] magrittr_1.5 checkmate_1.8.5 cluster_2.0.6
[13] sfsmisc_1.1-1 recipes_0.1.1 modelr_0.1.1
[16] gower_0.1.2 dimRed_0.1.0 sandwich_2.4-0
[19] colorspace_1.3-2 haven_1.1.0 crayon_1.3.4
[22] bindr_0.1 survival_2.41-3 iterators_1.0.8
[25] glue_1.2.0 DRR_0.0.2 gtable_0.2.0
[28] ipred_0.9-6 sjstats_0.13.0 kernlab_0.9-25
[31] ddalpha_1.3.1 DEoptimR_1.0-8 abind_1.4-5
[34] mvtnorm_1.0-6 ggeffects_0.3.0 Rcpp_0.12.14
[37] xtable_1.8-2 merTools_0.3.0 htmlTable_1.11.0
[40] foreign_0.8-69 Formula_1.2-2 stats4_3.4.2
[43] prediction_0.2.0 lava_1.5.1 survey_3.32-1
[46] prodlim_1.6.1 DT_0.2 htmlwidgets_0.9
[49] acepack_1.4.1 modeltools_0.2-21 pkgconfig_2.0.1
[52] nnet_7.3-12 labeling_0.3 tidyselect_0.2.3
[55] rlang_0.1.4 munsell_0.4.3 tools_3.4.2
[58] cli_1.0.0 sjlabelled_1.0.5 broom_0.4.3
[61] evaluate_0.10.1 stringr_1.2.0 arm_1.9-3
[64] yaml_2.1.15 ModelMetrics_1.1.0 robustbase_0.92-8
[67] caTools_1.17.1 purrr_0.2.4 coin_1.2-2
[70] mime_0.5 RcppRoll_0.2.2 compiler_3.4.2
[73] bayesplot_1.4.0 rstudioapi_0.7.0-9000 tibble_1.3.4
[76] stringi_1.1.6 highr_0.6 forcats_0.2.0
[79] psych_1.7.8 nloptr_1.0.4 effects_4.0-0
[82] stringdist_0.9.4.6 pwr_1.2-1 lmtest_0.9-35
[85] bitops_1.0-6 httpuv_1.3.5 R6_2.2.2
[88] latticeExtra_0.6-28 KernSmooth_2.23-15 codetools_0.2-15
[91] MASS_7.3-47 gtools_3.5.0 assertthat_0.2.0
[94] CVST_0.2-1 rprojroot_1.2 withr_2.1.0
[97] mnormt_1.5-5 multcomp_1.4-8 parallel_3.4.2
[100] grid_3.4.2 rpart_4.1-11 timeDate_3042.101
[103] coda_0.19-1 glmmTMB_0.2.0 class_7.3-14
[106] minqa_1.2.4 rmarkdown_1.8 snakecase_0.5.1
[109] carData_3.0-0 shiny_1.0.5 base64enc_0.1-3